From 9b30458f2f76db63d9e8f48fed1830131b2e4025 Mon Sep 17 00:00:00 2001 From: Barbara Suesser-Rechberger Date: Mon, 24 Jun 2024 18:22:59 +0200 Subject: [PATCH] SLR: New processing of SLR data with estimation of all relevant geodetic parameters. --- CHANGELOG.md | 18 + docs/documentation.pdf | Bin 18951457 -> 19007920 bytes docs/html/Cpf2Orbit.html | 90 ++ docs/html/Crd2NormalPoints.html | 89 ++ docs/html/Cstg2NormalPoints.html | 89 ++ docs/html/Merit2FullRate.html | 89 ++ docs/html/Merit2NormalPoints.html | 89 ++ docs/html/Orbit2Cpf.html | 91 ++ docs/html/PlatformCreate.html | 6 +- .../PreprocessingVariationalEquation.html | 4 +- docs/html/SinexEccentricties2SlrPlatform.html | 89 ++ ...SlrComModel2RangeBiasStationSatellite.html | 98 ++ docs/html/SlrProcessing.html | 100 ++ docs/html/SlrSinexDataHandling2Files.html | 94 ++ docs/html/classes.html | 4 + docs/html/documentationSearchIndex.js | 26 +- docs/html/instrumentTypeType.html | 2 + docs/html/platformSelectorType.html | 2 +- docs/html/programType.html | 13 + docs/html/slrParametrizationType.html | 382 ++++++ docs/html/slrProcessingStepType.html | 278 +++++ docs/html/slrSatelliteGeneratorType.html | 99 ++ docs/html/slrStationGeneratorType.html | 131 ++ docs/html/troposphereType.html | 11 + docs/latex/classes.auto.tex | 1035 ++++++++++++++-- docs/latex/programs.auto.tex | 257 +++- groops.xsd | 1077 ++++++++++++++++- .../classes/instrumentType/instrumentType.cpp | 36 +- .../miscAccelerationsAtmosphericDrag.h | 6 +- .../miscAccelerationsRadiationPressure.h | 154 +-- .../platformSelector/platformSelector.h | 2 +- source/classes/troposphere/troposphere.cpp | 10 +- source/classes/troposphere/troposphere.h | 27 +- source/classes/troposphere/troposphereGpt.cpp | 12 +- source/classes/troposphere/troposphereGpt.h | 14 +- .../troposphere/troposphereMendesAndPavlis.h | 301 +++++ .../troposphere/troposphereViennaMapping.cpp | 12 +- .../troposphere/troposphereViennaMapping.h | 14 +- source/files/fileInstrument.cpp | 268 ++-- source/files/fileInstrument.h | 92 +- .../gnssParametrizationTroposphere.cpp | 20 +- source/groops.cpp | 3 + source/inputOutput/fileSinex.cpp | 2 + .../misc/observation/variationalEquation.cpp | 37 +- source/misc/observation/variationalEquation.h | 19 +- .../variationalEquationFromFile.cpp | 2 +- source/parallel/matrixDistributed.h | 1 + .../gnss/gnssStationLog2StationInfo.cpp | 2 +- .../gnss/sinex2StationPositions.cpp | 6 +- source/programs/conversion/slr/cpf2Orbit.cpp | 201 +++ .../conversion/slr/crd2NormalPoints.cpp | 273 +++++ .../conversion/slr/cstg2NormalPoints.cpp | 256 ++++ .../conversion/slr/merit2FullRate.cpp | 201 +++ .../conversion/slr/merit2NormalPoints.cpp | 227 ++++ source/programs/conversion/slr/orbit2Cpf.cpp | 121 ++ .../slr/sinexEccentricties2SlrPlatform.cpp | 149 +++ .../slrComModel2RangeBiasStationSatellite.cpp | 142 +++ .../slr/slrSinexDataHandling2Files.cpp | 212 ++++ source/programs/misc/platformCreate.cpp | 6 +- .../preprocessingVariationalEquation.cpp | 14 +- source/programs/program.h | 1 + source/programs/slr/slrProcessing.cpp | 132 ++ source/slr/slr.cpp | 311 +++++ source/slr/slr.h | 95 ++ source/slr/slrDesignMatrix.cpp | 248 ++++ source/slr/slrDesignMatrix.h | 54 + source/slr/slrNormalEquationInfo.cpp | 141 +++ source/slr/slrNormalEquationInfo.h | 83 ++ source/slr/slrObservation.cpp | 235 ++++ source/slr/slrObservation.h | 94 ++ .../slrParametrization/slrParametrization.cpp | 288 +++++ .../slrParametrization/slrParametrization.h | 170 +++ .../slrParametrizationConstraints.h | 120 ++ .../slrParametrizationDynamicOrbits.cpp | 323 +++++ .../slrParametrizationDynamicOrbits.h | 105 ++ .../slrParametrizationEarthRotation.cpp | 343 ++++++ .../slrParametrizationEarthRotation.h | 77 ++ .../slrParametrizationGravityField.cpp | 142 +++ .../slrParametrizationGravityField.h | 63 + .../slrParametrizationGroup.h | 206 ++++ .../slrParametrizationRangeBiasSatellite.h | 254 ++++ ...ParametrizationRangeBiasSatelliteApriori.h | 130 ++ .../slrParametrizationRangeBiasStation.h | 255 ++++ ...lrParametrizationRangeBiasStationApriori.h | 135 +++ ...ParametrizationRangeBiasStationSatellite.h | 277 +++++ ...rizationRangeBiasStationSatelliteApriori.h | 144 +++ .../slrParametrizationStaticPositions.cpp | 390 ++++++ .../slrParametrizationStaticPositions.h | 88 ++ .../slrParametrizationTimeBias.cpp | 177 +++ .../slrParametrizationTimeBias.h | 68 ++ .../slrParametrizationTimeBiasApriori.h | 125 ++ .../slrParametrizationTroposphere.cpp | 284 +++++ .../slrParametrizationTroposphere.h | 82 ++ source/slr/slrPlatform.h | 97 ++ .../slrProcessingStep/slrProcessingStep.cpp | 438 +++++++ .../slr/slrProcessingStep/slrProcessingStep.h | 128 ++ .../slrProcessingStepEstimate.h | 125 ++ .../slrProcessingStepGroup.h | 80 ++ ...slrProcessingStepPrintResidualStatistics.h | 124 ++ .../slrProcessingStepSelectParametrizations.h | 124 ++ .../slrProcessingStepSelectSatellites.h | 81 ++ .../slrProcessingStepSelectStations.h | 81 ++ .../slrProcessingStepWriteAprioriSolution.h | 102 ++ .../slrProcessingStepWriteNormalEquations.h | 166 +++ .../slrProcessingStepWriteResiduals.h | 117 ++ .../slrProcessingStepWriteResults.h | 73 ++ .../slrProcessingStepWriteUsedSatelliteList.h | 84 ++ .../slrProcessingStepWriteUsedStationList.h | 84 ++ source/slr/slrSatellite.h | 135 +++ .../slrSatelliteGenerator.cpp | 76 ++ .../slrSatelliteGenerator.h | 96 ++ .../slrSatelliteGeneratorSatellites.cpp | 125 ++ .../slrSatelliteGeneratorSatellites.h | 55 + source/slr/slrStation.cpp | 116 ++ source/slr/slrStation.h | 80 ++ .../slrStationGenerator.cpp | 112 ++ .../slrStationGenerator/slrStationGenerator.h | 116 ++ .../slrStationGeneratorStations.cpp | 211 ++++ .../slrStationGeneratorStations.h | 91 ++ source/sourcesCXX.txt | 28 + 120 files changed, 15481 insertions(+), 409 deletions(-) create mode 100644 docs/html/Cpf2Orbit.html create mode 100644 docs/html/Crd2NormalPoints.html create mode 100644 docs/html/Cstg2NormalPoints.html create mode 100644 docs/html/Merit2FullRate.html create mode 100644 docs/html/Merit2NormalPoints.html create mode 100644 docs/html/Orbit2Cpf.html create mode 100644 docs/html/SinexEccentricties2SlrPlatform.html create mode 100644 docs/html/SlrComModel2RangeBiasStationSatellite.html create mode 100644 docs/html/SlrProcessing.html create mode 100644 docs/html/SlrSinexDataHandling2Files.html create mode 100644 docs/html/slrParametrizationType.html create mode 100644 docs/html/slrProcessingStepType.html create mode 100644 docs/html/slrSatelliteGeneratorType.html create mode 100644 docs/html/slrStationGeneratorType.html create mode 100755 source/classes/troposphere/troposphereMendesAndPavlis.h create mode 100644 source/programs/conversion/slr/cpf2Orbit.cpp create mode 100644 source/programs/conversion/slr/crd2NormalPoints.cpp create mode 100644 source/programs/conversion/slr/cstg2NormalPoints.cpp create mode 100644 source/programs/conversion/slr/merit2FullRate.cpp create mode 100644 source/programs/conversion/slr/merit2NormalPoints.cpp create mode 100644 source/programs/conversion/slr/orbit2Cpf.cpp create mode 100644 source/programs/conversion/slr/sinexEccentricties2SlrPlatform.cpp create mode 100644 source/programs/conversion/slr/slrComModel2RangeBiasStationSatellite.cpp create mode 100644 source/programs/conversion/slr/slrSinexDataHandling2Files.cpp create mode 100644 source/programs/slr/slrProcessing.cpp create mode 100644 source/slr/slr.cpp create mode 100644 source/slr/slr.h create mode 100644 source/slr/slrDesignMatrix.cpp create mode 100644 source/slr/slrDesignMatrix.h create mode 100644 source/slr/slrNormalEquationInfo.cpp create mode 100644 source/slr/slrNormalEquationInfo.h create mode 100644 source/slr/slrObservation.cpp create mode 100644 source/slr/slrObservation.h create mode 100644 source/slr/slrParametrization/slrParametrization.cpp create mode 100644 source/slr/slrParametrization/slrParametrization.h create mode 100644 source/slr/slrParametrization/slrParametrizationConstraints.h create mode 100644 source/slr/slrParametrization/slrParametrizationDynamicOrbits.cpp create mode 100644 source/slr/slrParametrization/slrParametrizationDynamicOrbits.h create mode 100644 source/slr/slrParametrization/slrParametrizationEarthRotation.cpp create mode 100644 source/slr/slrParametrization/slrParametrizationEarthRotation.h create mode 100644 source/slr/slrParametrization/slrParametrizationGravityField.cpp create mode 100644 source/slr/slrParametrization/slrParametrizationGravityField.h create mode 100644 source/slr/slrParametrization/slrParametrizationGroup.h create mode 100644 source/slr/slrParametrization/slrParametrizationRangeBiasSatellite.h create mode 100644 source/slr/slrParametrization/slrParametrizationRangeBiasSatelliteApriori.h create mode 100644 source/slr/slrParametrization/slrParametrizationRangeBiasStation.h create mode 100644 source/slr/slrParametrization/slrParametrizationRangeBiasStationApriori.h create mode 100644 source/slr/slrParametrization/slrParametrizationRangeBiasStationSatellite.h create mode 100644 source/slr/slrParametrization/slrParametrizationRangeBiasStationSatelliteApriori.h create mode 100644 source/slr/slrParametrization/slrParametrizationStaticPositions.cpp create mode 100644 source/slr/slrParametrization/slrParametrizationStaticPositions.h create mode 100644 source/slr/slrParametrization/slrParametrizationTimeBias.cpp create mode 100644 source/slr/slrParametrization/slrParametrizationTimeBias.h create mode 100644 source/slr/slrParametrization/slrParametrizationTimeBiasApriori.h create mode 100644 source/slr/slrParametrization/slrParametrizationTroposphere.cpp create mode 100644 source/slr/slrParametrization/slrParametrizationTroposphere.h create mode 100644 source/slr/slrPlatform.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStep.cpp create mode 100644 source/slr/slrProcessingStep/slrProcessingStep.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepEstimate.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepGroup.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepPrintResidualStatistics.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepSelectParametrizations.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepSelectSatellites.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepSelectStations.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepWriteAprioriSolution.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepWriteNormalEquations.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepWriteResiduals.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepWriteResults.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepWriteUsedSatelliteList.h create mode 100644 source/slr/slrProcessingStep/slrProcessingStepWriteUsedStationList.h create mode 100644 source/slr/slrSatellite.h create mode 100644 source/slr/slrSatelliteGenerator/slrSatelliteGenerator.cpp create mode 100644 source/slr/slrSatelliteGenerator/slrSatelliteGenerator.h create mode 100644 source/slr/slrSatelliteGenerator/slrSatelliteGeneratorSatellites.cpp create mode 100644 source/slr/slrSatelliteGenerator/slrSatelliteGeneratorSatellites.h create mode 100644 source/slr/slrStation.cpp create mode 100644 source/slr/slrStation.h create mode 100644 source/slr/slrStationGenerator/slrStationGenerator.cpp create mode 100644 source/slr/slrStationGenerator/slrStationGenerator.h create mode 100644 source/slr/slrStationGenerator/slrStationGeneratorStations.cpp create mode 100644 source/slr/slrStationGenerator/slrStationGeneratorStations.h diff --git a/CHANGELOG.md b/CHANGELOG.md index 37cbf6b8..0302fafa 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -2,6 +2,24 @@ - Interface change: Variables can now declared at any place in the config file (not only in the global section). They have local scope within the hierarchy level. Loop and conditions attributed to elements no longer need to be declared in the global section. +- SLR Processing: New processing of SLR data with estimation of all relevant geodetic parameters. + - New program: SlrProcessing + - New program: conversion: Cpf2Orbit + - New program: conversion: Crd2NormalPoints + - New program: conversion: Cstg2NormalPoints + - New program: conversion: Merit2FullRate + - New program: conversion: Merit2NormalPoints + - New program: conversion: Orbit2Cpf + - New program: conversion: SinexEccentricties2SlrPlatform + - New program: conversion: SlrComModel2RangeBiasStationSatellite + - New program: conversion: SlrSinexDataHandling2Files + - New class: slrParametrization + - New class: slrProcessingStep + - New class: slrSatelliteGenerator + - New class: slrStationGenerator + - New class: In Troposphere: MendesAndPavlis + - New instrument file format: SATELLITELASERRANGING + - New instrument file format: METEOROLOGICAL - New program: eclipseFactor2GriddedData.cpp: returns a global grid with eclipse factors. - New program: orbit2EarhFixedOrbit: Rotate an orbit into a rotation earth fixed frame. - New program: GriddedDataTimeSeries2PotentialCoefficients. diff --git a/docs/documentation.pdf b/docs/documentation.pdf index a682c6c795a46d9c7326f6c6b73eb75d7363f130..3401dcf0ded79cf91271a396e8a98e08804bdea4 100644 GIT binary patch delta 545905 zcmYhCbyVF@)30%NcXvOydvSLw4u#_G9NgUw#VPJ`aM$AQh2lmZKX#I} z_w1Qutz`1d&M$?(!w~CJqY#t6faa{Z7=hjT%5Lkt7~N;O+nGk@{?LCdITwD{X3M8~ z?;ak;vdpy*1+-lZQBQ9>~LF^|w@ zo)#j<=yIQYPmAY`=95k*tmJz116Q2>->5?40Km@qK9vKK64)jvdV@7vVnO!qnsjEC z5}Aup({&i9R0UBP(uI_p9$`DH*$)HBVVOcx)Ycb&OWjXv^c^yvcq1uM;0HPjl&7u5 zHllMOYbK_tlpz(ozs*qva)<~Kqzbo>co6Pa0iF=x4x1}VCV*rVrVXGmU}ZWYcM8QV z^?-z7nHGw~0kkYY;X~uY_2{3%a>86^5W@joJ-6U9CNfHecPG zgtA;M#f>;?omWYv8@EsZLtn=t^#m(d~a282f07f8q~>2u%bg?!GjF<0cG zXN;04NX_WLz=_e!RA00K_`YQ18a1TGE|D{Py8bd&z8FEze!h>u|cy{n(zu5Xna)@$_FCmoa*O-u$FQt4C=1sDPhZ2L2 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+ +
+
+
+

Cpf2Orbit

+ +Converts CPF file +and writes an instrument file (ORBIT).

The time format of the CPF file is UTC. +The coordinate system used in the CPF format is usually represented in TRF. +If earthRotation is provided the data are transformed +from terrestrial (TRF) to celestial reference frame (CRF).

See also Orbit2Cpf +

+ + + + + +
NameTypeAnnotation
outputfileOrbit
filename
earthRotation
earthRotation
inputfile
filenameSLR CPF file
+ +
+
+ + diff --git a/docs/html/Crd2NormalPoints.html b/docs/html/Crd2NormalPoints.html new file mode 100644 index 00000000..f8c1355e --- /dev/null +++ b/docs/html/Crd2NormalPoints.html @@ -0,0 +1,89 @@ + + + + + GROOPS - Crd2NormalPoints + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

Crd2NormalPoints

+ +Converts CRD file +and writes an instrument file (METEOROLOGICAL) including meteorological data like +temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) +including normal point data like range, accuracy, redundancy, wavelength and window size. +

+ + + + + +
NameTypeAnnotation
outputfileNormalPoints
filenamevariable {station} available
outputfileMeteorological
filenamevariable {station} available
inputfileSlrData
filenameSLR CRD files
+ +
+
+ + diff --git a/docs/html/Cstg2NormalPoints.html b/docs/html/Cstg2NormalPoints.html new file mode 100644 index 00000000..6788b0e5 --- /dev/null +++ b/docs/html/Cstg2NormalPoints.html @@ -0,0 +1,89 @@ + + + + + GROOPS - Cstg2NormalPoints + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

Cstg2NormalPoints

+ +Converts CSTG file provided by the ILRS +and writes an instrument file (METEOROLOGICAL) including meteorological data like +temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) +including normal point data like range, accuracy, redundancy, wavelength and window size. +

+ + + + + +
NameTypeAnnotation
outputfileNormalPoints
filenamevariable {station} available
outputfileMeteorological
filenamevariable {station} available
inputfileSlrData
filenameSLR CSTG file
+ +
+
+ + diff --git a/docs/html/Merit2FullRate.html b/docs/html/Merit2FullRate.html new file mode 100644 index 00000000..abd2ccec --- /dev/null +++ b/docs/html/Merit2FullRate.html @@ -0,0 +1,89 @@ + + + + + GROOPS - Merit2FullRate + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

Merit2FullRate

+ +Converts MERIT II file +and writes an instrument file (METEOROLOGICAL) including meteorological data like +temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) +including full rate data like range, accuracy, wavelength, azimuth and elevation. +

+ + + + + +
NameTypeAnnotation
outputfileNormalPoints
filenamevariable {station} available
outputfileMeteorological
filenamevariable {station} available
inputfileSlrData
filenameSLR MERIT II file
+ +
+
+ + diff --git a/docs/html/Merit2NormalPoints.html b/docs/html/Merit2NormalPoints.html new file mode 100644 index 00000000..bceff08d --- /dev/null +++ b/docs/html/Merit2NormalPoints.html @@ -0,0 +1,89 @@ + + + + + GROOPS - Merit2NormalPoints + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

Merit2NormalPoints

+ +Converts MERIT II file +and writes an instrument file (METEOROLOGICAL) including meteorological data like +temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) +including normal point data like range, accuracy, redundancy, wavelength, window size, azimuth and elevation. +

+ + + + + +
NameTypeAnnotation
outputfileNormalPoints
filenamevariable {station} available
outputfileMeteorological
filenamevariable {station} available
inputfileSlrData
filenameSLR MERIT II file
+ +
+
+ + diff --git a/docs/html/Orbit2Cpf.html b/docs/html/Orbit2Cpf.html new file mode 100644 index 00000000..ad789ac3 --- /dev/null +++ b/docs/html/Orbit2Cpf.html @@ -0,0 +1,91 @@ + + + + + GROOPS - Orbit2Cpf + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

Orbit2Cpf

+ +Writes groops orbits to CPF file.

The coordinate system used in the CPF format is usually presented in ITRF. +The required time format for the input orbit file is GPS. +The time format of the output CPF file is given in UTC.

See also Cpf2Orbit. +

+ + + + + + + + +
NameTypeAnnotation
outputfile
filename
inputfileOrbit
filename
inputfileSatelliteInfo
filenamePlatform File
earthRotation
earthRotation
versionNumber
uintVersion number of production day with zero leading fill, e.g. 01
targetClass
uintset 1 for passive retroreflector, set 0 for no retroreflector (includes debris)
+ +
+
+ + diff --git a/docs/html/PlatformCreate.html b/docs/html/PlatformCreate.html index fc91435e..18d41cf1 100644 --- a/docs/html/PlatformCreate.html +++ b/docs/html/PlatformCreate.html @@ -139,9 +139,9 @@

PlatformCreate

comment
string
timeStart
time
timeEnd
time -
positionX
double[m] exccentricity in north -
positionY
double[m] exccentricity in east -
positionZ
double[m] exccentricity in up +
positionX
double[m] eccentricity in north +
positionY
double[m] eccentricity in east +
positionZ
double[m] eccentricity in up
satelliteIdentifier
sequence
name
string
serial
string diff --git a/docs/html/PreprocessingVariationalEquation.html b/docs/html/PreprocessingVariationalEquation.html index a3ab0944..400b13c6 100644 --- a/docs/html/PreprocessingVariationalEquation.html +++ b/docs/html/PreprocessingVariationalEquation.html @@ -77,7 +77,7 @@

PreprocessingVariationalEquation

This means for each arc new initial state parameters are setup.

In a first step the forces acting on the satellite are evaluated at the apriori positions given by inputfileOrbit. Non-conservative forces like solar radiation pressure needs the orientation of the satellite (inputfileStarCamera) and additional a satellite macro model (satelliteModel) -with the surface properties. Furthermore inputfileAccelerometer observations are also considered.

In a second step the accelerations are integrated twice to an dynamic orbit unsing a moving polynomial with the degree +with the surface properties. Furthermore inputfileAccelerometer observations are also considered.

In a second step the accelerations are integrated twice to an dynamic orbit using a moving polynomial with the degree integrationDegree. The orbit is corrected to be self-consistent. This means the forces should be evaluated at the new integrated positions instead of the apriori ones. This correction is computed in a linear approximation using the gradient of the forces with respect to the positions (gradientfield). As this term is small generally @@ -90,7 +90,7 @@

PreprocessingVariationalEquation

afterwards more digits are available for the computation.

The integrated orbit should be fitted to observations afterwards by the programs PreprocessingVariationalEquationOrbitFit and/or PreprocessingVariationalEquationSstFit. They apply a least squares adjustment by estimating some satellite parameters (e.g. an accelerometer bias). -If the fitted orbit is to far away from the original inputfileOrbit the linearization may not be +If the fitted orbit is too far away from the original inputfileOrbit the linearization may not be accurate enough. In this case PreprocessingVariationalEquation should be run again with the fitted orbit as inputfileOrbit and introducing the estimatedParameters as additional forces.

diff --git a/docs/html/SinexEccentricties2SlrPlatform.html b/docs/html/SinexEccentricties2SlrPlatform.html new file mode 100644 index 00000000..31a0f2eb --- /dev/null +++ b/docs/html/SinexEccentricties2SlrPlatform.html @@ -0,0 +1,89 @@ + + + + + GROOPS - SinexEccentricties2SlrPlatform + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

SinexEccentricties2SlrPlatform

+ +Reads metadata like station name, station number, approximate station position and station eccentricities +from Station Eccentricities Sinex File +(une version) and write them to the outputfileStationInfo for each station. +

+ + + + + + +
NameTypeAnnotation
outputfileStationInfo
filenameloop variable is replaced with station name
variableLoopStation
stringvariable name for station loop
inputfileSinex
filenameSINEX file (.snx or .ssc)
stationName
stringconvert only these stations
+ +
+
+ + diff --git a/docs/html/SlrComModel2RangeBiasStationSatellite.html b/docs/html/SlrComModel2RangeBiasStationSatellite.html new file mode 100644 index 00000000..e5f4e405 --- /dev/null +++ b/docs/html/SlrComModel2RangeBiasStationSatellite.html @@ -0,0 +1,98 @@ + + + + + GROOPS - SlrComModel2RangeBiasStationSatellite + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

SlrComModel2RangeBiasStationSatellite

+ +Converts the tables of CoM corrections of José Rodríguez +(https://icts-yebes.oan.es/slr/com_models/models/) into station/satellite +specific outputfileRangeBias. Only the deviations to the default value in +inputfileSatelliteInfo are written. This program must be called for every +provided satellite. The range bias values can be used in +parametrization:rangeBiasStationSatelliteApriori +in SlrProcessing.

Reference: +Rodriguez J., Otsubo T., Appleby G. Upgraded Modelling for the +Determination of Centre of Mass Corrections of Geodetic SLR +Satellites: Impact on Key Parameters of the Terrestrial Reference +Frame. Journal of Geodesy, 2019. doi: 10.1007/s00190-019-01315-0 +

+ + + + + + + +
NameTypeAnnotation
outputfileRangeBias
filenameMISCVALUE, variable {station} available
inputfileSatelliteInfo
filename
inputfile
filenamefrom Rodriguez model
variableLoopStation
stringvariable name for station loop
stationName
stringconvert only these stations
+ +
+
+ + diff --git a/docs/html/SlrProcessing.html b/docs/html/SlrProcessing.html new file mode 100644 index 00000000..2d38abfb --- /dev/null +++ b/docs/html/SlrProcessing.html @@ -0,0 +1,100 @@ + + + + + GROOPS - SlrProcessing + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

SlrProcessing

+ +This program processes SLR normal point or full rate observations. It calculates the linearized observation equations, +accumulates them into a system of normal equations and solves it.

To calculate observation equations from the passes, the model parameters or unknown parameters need to be +defined beforehand. These unknown parameters can be chosen arbitrarily by the user with an adequate list of defined +parametrization. +Some of the parametrization also include a priori models.

Lastly it is required to define the process flow of the SLR processing. This is accomplished +with a list of processingSteps. +Each step is processed consecutively. Some steps allow the selection of parameters, station, or satellites, +which affects all subsequent steps.

The timeSeries is used to precompute Earth rotation and station displacements +with a uniform sampling. In a second step these values are interpolated to the observation epochs. +A sampling of about 10 minutes should be adequate.

It should be noted that GROOPS uses GPS time format, but normal point/full rate data files and CPF files, provided by ILRS data centers +are given in UTC time format. + +

+ + + + + + + + +
NameTypeAnnotation
timeSeries
timeSeriesdefines station movements and earth rotation epochs
satellite
slrSatelliteGeneratorsatellites
station
slrStationGeneratorground station network
earthRotation
earthRotationapriori earth rotation
parametrization
slrParametrizationmodels and parameters
processingStep
slrProcessingStepsteps are processed consecutively
+ +
+
+ + diff --git a/docs/html/SlrSinexDataHandling2Files.html b/docs/html/SlrSinexDataHandling2Files.html new file mode 100644 index 00000000..21657a0f --- /dev/null +++ b/docs/html/SlrSinexDataHandling2Files.html @@ -0,0 +1,94 @@ + + + + + GROOPS - SlrSinexDataHandling2Files + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+
+

SlrSinexDataHandling2Files

+ +Converts SLR range and time bias from ILRS_Data_Handling_File_xxxx.xx.xx.snx provided at +https://cddis.nasa.gov/archive/slr/products/resource/. The range and time bias values can be used in +parametrization:rangeBiasXxxApriori +in SlrProcessing. +

+ + + + + + + + + + +
NameTypeAnnotation
outputfileRangeBiasStation
filenameMISCVALUE [m]
outputfileRangeBiasStationSatellite
filenameMISCVALUE [m]
outputfileTimeBias
filenameMISCVALUES(bias [s], drift [s/d])
variableLoopStation
stringvariable name for station loop
variableLoopSatellite
stringvariable name for satellite loop
inputfileSinex
filenameSINEX file (.snx)
inputfileSatelliteId
filenametable SP3 and satellite name
stationName
stringconvert only these stations
+ +
+
+ + diff --git a/docs/html/classes.html b/docs/html/classes.html index 81988e19..f3975f27 100644 --- a/docs/html/classes.html +++ b/docs/html/classes.html @@ -123,6 +123,10 @@

Classes

  • plotSymbol
  • podRightSide
  • sggRightSide
  • +
  • slrParametrization
  • +
  • slrProcessingStep
  • +
  • slrSatelliteGenerator
  • +
  • slrStationGenerator
  • sphericalHarmonicsFilter
  • sphericalHarmonicsNumbering
  • sstRightSide
  • diff --git a/docs/html/documentationSearchIndex.js b/docs/html/documentationSearchIndex.js index 9a62a8ad..2a631aa2 100644 --- a/docs/html/documentationSearchIndex.js +++ b/docs/html/documentationSearchIndex.js @@ -154,7 +154,7 @@ var documents = { 'MagneticField2GriddedData': { 'name': 'MagneticField2GriddedData', 'key': 'MagneticField2GriddedData', 'description': 'Computes x, y, z of the magentic field vector.', 'config_table': 'outputfileGriddedData filename x, y, z [Tesla = kg/A/s**2] magnetosphere magnetosphereType grid gridType time time localReferenceFrame boolean local left handed reference frame (north, east, up) R double reference radius for ellipsoidal coordinates on output inverseFlattening double reference flattening for ellipsoidal coordinates on output, 0: spherical coordinates', 'display_text': 'Computes x, y, z of the magentic field vector.'}, 'MatrixCalculate': { 'name': 'MatrixCalculate', 'key': 'MatrixCalculate', 'description': 'This program creates a matrix from multiple matrices. All This program creates a are summed up. The size of the resulting matrix is exandeded to fit all matrices. The class This program creates a allows complex matrix operations before.', 'config_table': 'outputfileMatrix filename matrix matrixGeneratorType', 'display_text': 'This program creates a matrix from multiple matrices. All matrices are summed up. The size of the resulting matrix is exandeded to fit all matrices. The class matrixGenerator allows complex matrix operations before.'}, 'ObservationEquations2Files': { 'name': 'ObservationEquations2Files', 'key': 'ObservationEquations2Files', 'description': 'This program computes the linearized and decorrelated equation system for each arc : using class This program computes the linearized and decorrelated equation system for each arc and writes , and as matrix files.', 'config_table': 'outputfileObservationVector filename one file for each arc outputfileDesignMatrix filename one file for each arc, without arc related parameters outputfileDesignMatrixArc filename one file for each arc, arc related parameters variableArc string variable with arc number outputfileParameterNames filename without arc related parameters observation observationType', 'display_text': 'This program computes the linearized and decorrelated equation system for each arc $i$: \\[ \\M l_i = \\M A_i \\M x + \\M B_i \\M y_i + \\M e_i \\]using class observation and writes $\\M A_i$, $\\M B_i$ and $\\M l_i$ as matrix files.'}, -'PlatformCreate': { 'name': 'PlatformCreate', 'key': 'PlatformCreate', 'description': 'Create a Platform file from scratch by defining attributes such as markerName , markerNumber , comment , approxPosition , equipment . See also GnssAntex2AntennaDefinition and GnssStationLog2Platform .', 'config_table': 'outputfilePlatform filename markerName string markerNumber string comment string approxPositionX double [m] in TRF approxPositionY double [m] in TRF approxPositionZ double [m] in TRF equipment choice gnssAntenna sequence name string serial string radome string comment string timeStart time timeEnd time positionX double [m] ARP in north, east, up or vehicle system positionY double [m] ARP in north, east, up or vehicle system positionZ double [m] ARP in north, east, up or vehicle system rotationX angle [degree] from local/vehicle to left-handed antenna system rotationY angle [degree] from local/vehicle to left-handed antenna system rotationZ angle [degree] from local/vehicle to left-handed antenna system flipX boolean flip x-axis (after rotation) flipY boolean flip y-axis (after rotation) flipZ boolean flip z-axis (after rotation) gnssReceiver sequence name string serial string version string comment string timeStart time timeEnd time laserRetroReflector sequence name string e.g. GFZ, ITE, IPIE serial string comment string timeStart time timeEnd time positionX double [m] optial reference point RP in satellite system positionY double [m] optial reference point RP in satellite system positionZ double [m] optial reference point RP in satellite system rotationX angle [degree] from local/vehicle to LRR system rotationY angle [degree] from local/vehicle to LRR system rotationZ angle [degree] from local/vehicle to LRR system flipX boolean flip x-axis (after rotation) flipY boolean flip y-axis (after rotation) flipZ boolean flip z-axis (after rotation) range double [m] range bias (only without range matrix) inputfileRangeMatrix filename [m] (azimuth(0..360) x zenith(0..dZenit*rows) dZenit angle [degree] increment of range matrix geodeticSatellite sequence e.g. LAGEOS name string serial string comment string timeStart time timeEnd time range double [m] standard center-of-mass correction slrStation sequence name string CDP SOD 8-digit No. serial string IERS DOMES comment string timeStart time timeEnd time positionX double [m] exccentricity in north positionY double [m] exccentricity in east positionZ double [m] exccentricity in up satelliteIdentifier sequence name string serial string cospar string Satellite COSPAR ID norad string Satellite Catalog (NORAD) Number sic string SIC Code sp3 string SP3 comment string timeStart time timeEnd time other sequence name string serial string comment string timeStart time timeEnd time positionX double [m] in north, east, up or vehicle system positionY double [m] in north, east, up or vehicle system positionZ double [m] in north, east, up or vehicle system referencePoint sequence e.g. center of mass in satellite frame comment string xStart double [m] in north, east, up or vehicle system yStart double linear motion between start and end zStart double xEnd double [m] in north, east, up or vehicle system yEnd double linear motion between start and end zEnd double timeStart time timeEnd time', 'display_text': 'Create a Platform file from scratch by defining attributes such as markerName, markerNumber, comment, approxPosition, equipment.

    See also GnssAntex2AntennaDefinition and GnssStationLog2Platform.

    '}, +'PlatformCreate': { 'name': 'PlatformCreate', 'key': 'PlatformCreate', 'description': 'Create a Platform file from scratch by defining attributes such as markerName , markerNumber , comment , approxPosition , equipment . See also GnssAntex2AntennaDefinition and GnssStationLog2Platform .', 'config_table': 'outputfilePlatform filename markerName string markerNumber string comment string approxPositionX double [m] in TRF approxPositionY double [m] in TRF approxPositionZ double [m] in TRF equipment choice gnssAntenna sequence name string serial string radome string comment string timeStart time timeEnd time positionX double [m] ARP in north, east, up or vehicle system positionY double [m] ARP in north, east, up or vehicle system positionZ double [m] ARP in north, east, up or vehicle system rotationX angle [degree] from local/vehicle to left-handed antenna system rotationY angle [degree] from local/vehicle to left-handed antenna system rotationZ angle [degree] from local/vehicle to left-handed antenna system flipX boolean flip x-axis (after rotation) flipY boolean flip y-axis (after rotation) flipZ boolean flip z-axis (after rotation) gnssReceiver sequence name string serial string version string comment string timeStart time timeEnd time laserRetroReflector sequence name string e.g. GFZ, ITE, IPIE serial string comment string timeStart time timeEnd time positionX double [m] optial reference point RP in satellite system positionY double [m] optial reference point RP in satellite system positionZ double [m] optial reference point RP in satellite system rotationX angle [degree] from local/vehicle to LRR system rotationY angle [degree] from local/vehicle to LRR system rotationZ angle [degree] from local/vehicle to LRR system flipX boolean flip x-axis (after rotation) flipY boolean flip y-axis (after rotation) flipZ boolean flip z-axis (after rotation) range double [m] range bias (only without range matrix) inputfileRangeMatrix filename [m] (azimuth(0..360) x zenith(0..dZenit*rows) dZenit angle [degree] increment of range matrix geodeticSatellite sequence e.g. LAGEOS name string serial string comment string timeStart time timeEnd time range double [m] standard center-of-mass correction slrStation sequence name string CDP SOD 8-digit No. serial string IERS DOMES comment string timeStart time timeEnd time positionX double [m] eccentricity in north positionY double [m] eccentricity in east positionZ double [m] eccentricity in up satelliteIdentifier sequence name string serial string cospar string Satellite COSPAR ID norad string Satellite Catalog (NORAD) Number sic string SIC Code sp3 string SP3 comment string timeStart time timeEnd time other sequence name string serial string comment string timeStart time timeEnd time positionX double [m] in north, east, up or vehicle system positionY double [m] in north, east, up or vehicle system positionZ double [m] in north, east, up or vehicle system referencePoint sequence e.g. center of mass in satellite frame comment string xStart double [m] in north, east, up or vehicle system yStart double linear motion between start and end zStart double xEnd double [m] in north, east, up or vehicle system yEnd double linear motion between start and end zEnd double timeStart time timeEnd time', 'display_text': 'Create a Platform file from scratch by defining attributes such as markerName, markerNumber, comment, approxPosition, equipment.

    See also GnssAntex2AntennaDefinition and GnssStationLog2Platform.

    '}, 'PotentialCoefficients2BlockMeanTimeSplines': { 'name': 'PotentialCoefficients2BlockMeanTimeSplines', 'key': 'PotentialCoefficients2BlockMeanTimeSplines', 'description': 'This program is a simplified version of Gravityfield2TimeSplines . It reads a series of potential coefficient files ( This program is a simplified version of ) and creates a time splines file with spline degree 0 (temporal block means) or degree 1 (linear splines). The time intervals in which the potential coefficients are valid are defined between adjacent points in time given by splineTimeSeries . Therefore one more point in time is needed than the number of potential coefficient files for degree 0. The coefficients can be filtered with This program is a simplified version of . If set the expansion is limited in the range between minDegree and maxDegree inclusivly. The coefficients are related to the reference radius R and the Earth gravitational constant GM . This program is useful e.g. to combine monthly GRACE solutions to one file.', 'config_table': 'outputfileTimeSplines filename outputfileTimeSplinesCovariance filename only the variances are saved inputfilePotentialCoefficients filename filter sphericalHarmonicsFilterType minDegree uint maxDegree uint GM double Geocentric gravitational constant R double reference radius removeMean boolean remove the temporal mean of the series before estimating the splines interpolate boolean interpolate missing files splineTimeSeries timeSeriesType input files must be between points in time splineDegree uint degree of splines', 'display_text': 'This program is a simplified version of Gravityfield2TimeSplines. It reads a series of potential coefficient files (inputfilePotentialCoefficients) and creates a time splines file with spline degree 0 (temporal block means) or degree 1 (linear splines). The time intervals in which the potential coefficients are valid are defined between adjacent points in time given by splineTimeSeries. Therefore one more point in time is needed than the number of potential coefficient files for degree 0.

    The coefficients can be filtered with filter. If set the expansion is limited in the range between minDegree and maxDegree inclusivly. The coefficients are related to the reference radius R and the Earth gravitational constant GM.

    This program is useful e.g. to combine monthly GRACE solutions to one file.'}, 'PotentialCoefficients2DegreeAmplitudes': { 'name': 'PotentialCoefficients2DegreeAmplitudes', 'key': 'PotentialCoefficients2DegreeAmplitudes', 'description': 'This program computes degree amplitudes from potentialCoefficients files and saves them to a matrix file. The coefficients can be filtered with This program computes degree amplitudes from and converted to different functionals with This program computes degree amplitudes from . The gravity field can be evaluated at different altitudes by specifying evaluationRadius . Polar regions can be excluded by setting polarGap . If set the expansion is limited in the range between minDegree and maxDegree inclusivly. The coefficients are related to the reference radius R and the Earth gravitational constant GM . The This program computes degree amplitudes from contains in the first 3 columns the degree, the degree amplitude, and the formal errors. For each additional This program computes degree amplitudes from three columns are appended: the degree amplitude, the formal errors, and the difference to the first file. For example the data columns for 4 This program computes degree amplitudes from are degree= data0 PotentialCoefficients0: signal= data1 , error= data2 , PotentialCoefficients1: signal= data3 , error= data4 , difference= data5 , PotentialCoefficients2: signal= data6 , error= data7 , difference= data8 , PotentialCoefficients3: signal= data9 , error= data10 , difference= data11 . See also Gravityfield2DegreeAmplitudes .', 'config_table': 'outputfileMatrix filename matrix with degree, signal amplitude, formal error, differences inputfilePotentialCoefficients filename kernel kernelType filter sphericalHarmonicsFilterType filter the coefficients type choice type of variances rms degree amplitudes (square root of degree variances) accumulation cumulate variances over degrees evaluationRadius double evaluate the gravity field at this radius (default: evaluate at surface polarGap angle exclude polar regions (aperture angle in degrees) minDegree uint maxDegree uint GM double Geocentric gravitational constant R double reference radius', 'display_text': 'This program computes degree amplitudes from potentialCoefficients files and saves them to a matrix file.

    The coefficients can be filtered with filter and converted to different functionals with kernel. The gravity field can be evaluated at different altitudes by specifying evaluationRadius. Polar regions can be excluded by setting polarGap. If set the expansion is limited in the range between minDegree and maxDegree inclusivly. The coefficients are related to the reference radius R and the Earth gravitational constant GM.

    The outputfileMatrix contains in the first 3 columns the degree, the degree amplitude, and the formal errors. For each additional inputfilePotentialCoefficients three columns are appended: the degree amplitude, the formal errors, and the difference to the first file.

    For example the data columns for 4 inputfilePotentialCoefficients are

    • degree=data0
    • PotentialCoefficients0: signal=data1, error=data2,
    • PotentialCoefficients1: signal=data3, error=data4, difference=data5,
    • PotentialCoefficients2: signal=data6, error=data7, difference=data8,
    • PotentialCoefficients3: signal=data9, error=data10, difference=data11.

    See also Gravityfield2DegreeAmplitudes.'}, 'RadialBasisSplines2KernelCoefficients': { 'name': 'RadialBasisSplines2KernelCoefficients', 'key': 'RadialBasisSplines2KernelCoefficients', 'description': 'This program calculates the coefficients of a This program calculates the coefficients according to from a given This program calculates the coefficients , with R and GM describing the reference radius and the geocentric constant, respectively. The stand for the gravity field accuracies (from degree minDegree to maxDegree ), if they are given. If no accuracies are provided, the represent the square root of the degree variances of the gravity field. If maxDegree exceeds the maximum degree given by This program calculates the coefficients , the higher degrees are complemented by Kaula\'s rule The output of the coefficients is given in the file This program calculates the coefficients .', 'config_table': 'outputfileCoefficients filename gravityfield gravityfieldType use sigmas, if not given use signal (cnm,snm), if not given use kaulas rule minDegree uint maxDegree uint GM double Geocentric gravitational constant R double reference radius kaulaPower double sigma = kaulaFactor/degree^kaulaPower kaulaFactor double sigma = kaulaFactor/degree^kaulaPower', 'display_text': 'This program calculates the coefficients $k_n$ of a kernel:coefficients according to \\[ k_n = \\frac{GM}{4\\pi R}\\frac{\\sigma_n}{\\sqrt{2n+1}}. \\]from a given gravityfield, with R and GM describing the reference radius and the geocentric constant, respectively. The $\\sigma_n$ stand for the gravity field accuracies (from degree minDegree to maxDegree), if they are given. If no accuracies are provided, the $\\sigma_n$ represent the square root of the degree variances of the gravity field. If maxDegree exceeds the maximum degree given by gravityfield, the higher degrees are complemented by Kaula\'s rule The output of the coefficients is given in the file outputfileCoefficients.'}, @@ -170,7 +170,7 @@ var documents = { 'NormalsCreate': { 'name': 'NormalsCreate', 'key': 'NormalsCreate', 'description': 'Create normal equations from calculated matrices ( Create ). The Create can be created with ParameterNamesCreate . The Create must be symmetric. The Create must have the same number of rows and can contain multiple columns for multiple solutions. The Vector is the quadratic sum of observations for each column of the right hand side. It is used to determine the aposteriori accuracy If the vector is not given, it is automatically determined by assuming . The number of observations is given by the expression observationCount . The variable observationCount can be used, if it is set by a normal equation file Create .', 'config_table': 'outputfileNormalEquation filename inputfileParameterNames filename normalMatrix matrixGeneratorType rightHandSide matrixGeneratorType lPl matrixGeneratorType vector with size of rhs columns inputfileNormalEquationObsCount filename sets the variable observationCount observationCount expression (variables: rows, columns (rhs), observationCount)', 'display_text': 'Create normal equations from calculated matrices (matrixGenerator).

    The inputfileParameterNames can be created with ParameterNamesCreate.

    The normalMatrix must be symmetric. The rightHandSide must have the same number of rows and can contain multiple columns for multiple solutions.

    The Vector $\\M l^T\\M P\\M l$ is the quadratic sum of observations for each column of the right hand side. It is used to determine the aposteriori accuracy \\[ \\hat{\\sigma}^2 = \\frac{\\hat{\\M e}^T\\M P\\hat{\\M e}}{n-m} = \\frac{\\M l^T\\M P\\M l - \\M n^T\\hat{\\M x}}{n-m}. \\]If the vector is not given, it is automatically determined by assuming $\\hat{\\sigma}^2=1$.

    The number of observations $n$ is given by the expression observationCount. The variable observationCount can be used, if it is set by a normal equation file inputfileNormalEquationObsCount.'}, 'NormalsEliminate': { 'name': 'NormalsEliminate', 'key': 'NormalsEliminate', 'description': 'This program eliminates parameters from a system of This program eliminates parameters from a system of s. To just remove (cutting out) parameters use NormalsReorder . The This program eliminates parameters from a system of allows the selection of parameters that will remain, all others will be eliminated. The order of remaining parameters can be modified via the parameter selection. Block size of the output normal matrix can be adjusted with outBlockSize . If it is set to zero, the This program eliminates parameters from a system of is written to a single block file. For example the normal equations are divided into two groups of parameters and according to and shall be eliminated, the reduced system of normal equations is given by See also NormalsReorder .', 'config_table': 'outputfileNormalEquation filename inputfileNormalEquation filename remainingParameters parameterSelectorType parameter order/selection of output normal equations outBlockSize uint block size for distributing the normal equations, 0: one block', 'display_text': 'This program eliminates parameters from a system of inputfileNormalEquations. To just remove (cutting out) parameters use NormalsReorder.

    The remainingParameters allows the selection of parameters that will remain, all others will be eliminated. The order of remaining parameters can be modified via the parameter selection. Block size of the output normal matrix can be adjusted with outBlockSize. If it is set to zero, the outputfileNormalEquation is written to a single block file.

    For example the normal equations are divided into two groups of parameters $\\hat{\\M x}_1$ and $\\hat{\\M x}_2$ according to \\[ \\begin{pmatrix} \\M N_{11} & \\M N_{12} \\\\ \\M N_{21} & \\M N_{22} \\end{pmatrix} \\begin{pmatrix} \\hat{\\M x}_1 \\\\ \\hat{\\M x}_2 \\end{pmatrix} = \\begin{pmatrix} \\M n_1 \\\\ \\M n_2 \\end{pmatrix}. \\]and $\\hat{\\M x}_2$ shall be eliminated, the reduced system of normal equations is given by \\[ \\bar{\\M N}\\hat{\\M x} = \\bar{\\M n} \\qquad\\text{with}\\qquad \\bar{\\M N}=\\M N_{11}-\\M N_{12}\\M N_{22}^{-1}\\M N_{12}^T \\qquad\\text{and}\\qquad\\bar{\\M n} = \\M n_1 - \\M N_{12}\\M N_{22}^{-1}\\M n_2. \\] See also NormalsReorder.'}, 'NormalsMultiplyAdd': { 'name': 'NormalsMultiplyAdd', 'key': 'NormalsMultiplyAdd', 'description': 'This program modifies This program modifies in a way that is estimated instead of . where is This program modifies and is factor . This can be used to re-add reduced reference fields before a combined estimation at normal equation level. Therefore the right hand side of the normal equations is modified by and the quadratic sum of observations by As the normal matrix itself is not modified, rewriting of the matrix can be disabled by setting writeNormalMatrix to false.', 'config_table': 'outputfileNormalEquation filename inputfileNormalEquation filename inputfileParameter filename x factor double alpha writeNormalMatrix boolean write full coefficient matrix, right hand sides and info files', 'display_text': 'This program modifies inputfileNormalEquation in a way that $\\bar{\\M x}$ is estimated instead of $\\M x$. \\[ \\bar{\\M x} := \\M x + \\alpha\\, \\M x_0, \\]where $\\M x_0$ is inputfileParameter and $\\alpha$ is factor. This can be used to re-add reduced reference fields before a combined estimation at normal equation level. Therefore the right hand side of the normal equations is modified by \\[ \\bar{\\M n} := \\M n + \\alpha\\,\\M N\\M x_0, \\]and the quadratic sum of observations by \\[ \\bar{\\M l^T\\M P\\M l} := \\M l^T\\M P\\M l + \\alpha^2\\,\\M x_0^T\\M N\\M x_0 + 2\\alpha\\,\\M x_0^T\\M n \\] As the normal matrix itself is not modified, rewriting of the matrix can be disabled by setting writeNormalMatrix to false.'}, -'NormalsRegularizationBorders': { 'name': 'NormalsRegularizationBorders', 'key': 'NormalsRegularizationBorders', 'description': 'This program sets up two regularization matrices for two different regional areas. For a given set of points defined by This program sets up two regularization matrices for two different regional areas. For a given set of points defined by it is evaluated, whether each point (corresponding to an unknown parameter of a respective parameterization by space localizing basis functions) is inside or outside a certain area given by This program sets up two regularization matrices for two different regional areas. For a given set of points defined by . Each regularization matrix is a diagonal matrix, one of them features a one if the point is inside, and a zero if the point lies outside the area. The other matrix features a zero if the point is inside, and a one if the point lies outside the area This results in two regularization matrices with The two matrices are provided as vectors of the diagonal in the output files This program sets up two regularization matrices for two different regional areas. For a given set of points defined by and This program sets up two regularization matrices for two different regional areas. For a given set of points defined by . The regularization matrices are then used by This program sets up two regularization matrices for two different regional areas. For a given set of points defined by . As an example, the two different areas could be oceanic regions on the one hand and continental areas on the other hand.', 'config_table': 'outputfileInside filename outputfileOutside filename grid gridType nodal point distribution of parameters, e.g harmonics splines border borderType regularization areas, e.g land and ocean', 'display_text': 'This program sets up two regularization matrices for two different regional areas. For a given set of points defined by grid it is evaluated, whether each point (corresponding to an unknown parameter of a respective parameterization by space localizing basis functions) is inside or outside a certain area given by border. Each regularization matrix is a diagonal matrix, one of them features a one if the point is inside, and a zero if the point lies outside the area. The other matrix features a zero if the point is inside, and a one if the point lies outside the area This results in two regularization matrices with \\[ \\M R_1+\\M R_2=\\M I. \\]The two matrices are provided as vectors of the diagonal in the output files outputfileOutside and outputfileInside. The regularization matrices are then used by normalEquation:regularization. As an example, the two different areas could be oceanic regions on the one hand and continental areas on the other hand.'}, +'NormalsRegularizationBorders': { 'name': 'NormalsRegularizationBorders', 'key': 'NormalsRegularizationBorders', 'description': 'This program sets up two regularization matrices for two different regional areas. For a given set of points defined by This program sets up two regularization matrices for two different regional areas. For a given set of points defined by it is evaluated, whether each point (corresponding to an unknown parameter of a respective parameterization by space localizing basis functions) is inside or outside a certain area given by This program sets up two regularization matrices for two different regional areas. For a given set of points defined by . Each regularization matrix is a diagonal matrix, one of them features a one if the point is inside, and a zero if the point lies outside the area. The other matrix features a zero if the point is inside, and a one if the point lies outside the area This results in two regularization matrices with The two matrices are provided as vectors of the diagonal in the output files This program sets up two regularization matrices for two different regional areas. For a given set of points defined by and This program sets up two regularization matrices for two different regional areas. For a given set of points defined by . The regularization matrices are then used by This program sets up two regularization matrices for two different regional areas. For a given set of points defined by . As an example, the two different areas could be oceanic regions on the one hand and continental areas on the other hand.', 'config_table': 'outputfileInside filename outputfileOutside filename grid gridType nodal point distribution of parameters, e.g harmonics splines border borderType regularization areas, e.g land and ocean R double reference radius for ellipsoidal coordinates for border inverseFlattening double reference flattening for ellipsoidal coordinates for border, 0: spherical coordinates', 'display_text': 'This program sets up two regularization matrices for two different regional areas. For a given set of points defined by grid it is evaluated, whether each point (corresponding to an unknown parameter of a respective parameterization by space localizing basis functions) is inside or outside a certain area given by border. Each regularization matrix is a diagonal matrix, one of them features a one if the point is inside, and a zero if the point lies outside the area. The other matrix features a zero if the point is inside, and a one if the point lies outside the area This results in two regularization matrices with \\[ \\M R_1+\\M R_2=\\M I. \\]The two matrices are provided as vectors of the diagonal in the output files outputfileOutside and outputfileInside. The regularization matrices are then used by normalEquation:regularization. As an example, the two different areas could be oceanic regions on the one hand and continental areas on the other hand.'}, 'NormalsRegularizationSphericalHarmonics': { 'name': 'NormalsRegularizationSphericalHarmonics', 'key': 'NormalsRegularizationSphericalHarmonics', 'description': 'Diagonal regularization matrix from gravity field accuracies, if not given from signal (cnm,snm), if not given from kaulas rule. The inverse accuracies are used as weights in the regularization matrix. The diagonal is saved as Vector. The corresponding pseudo observations can be computed with Gravityfield2SphericalHarmonicsVector .', 'config_table': 'outputfileDiagonalmatrix filename gravityfield gravityfieldType use sigmas, if not given use signal (cnm,snm), if not given use kaulas rule minRegularizationDegree uint maxRegularizationDegree uint minDegree uint maxDegree uint numbering sphericalHarmonicsNumberingType numbering scheme for regul matrix GM double Geocentric gravitational constant R double reference radius makeIsotropic boolean kaulaPower double sigma = kaulaFactor*degree**kaulaPower kaulaFactor double sigma = kaulaFactor*degree**kaulaPower', 'display_text': 'Diagonal regularization matrix from gravity field accuracies, if not given from signal (cnm,snm), if not given from kaulas rule. The inverse accuracies $1/\\sigma_n^2$ are used as weights in the regularization matrix. The diagonal is saved as Vector.

    The corresponding pseudo observations can be computed with Gravityfield2SphericalHarmonicsVector.'}, 'NormalsReorder': { 'name': 'NormalsReorder', 'key': 'NormalsReorder', 'description': 'Reorder Reorder by selecting parameters in a specific order. The Reorder also allows one to change dimension of the normal equations, either by cutting parameters or by inserting zero rows/columns for additional parameters. Without Reorder the order of parameters remains the same. Additionally the block sizes of the files can be adjusted. If outBlockSize is set to zero, the normal matrix is written to a single block file, which is needed by some programs. To eliminate parameters without changing the result of the other parameters use NormalsEliminate .', 'config_table': 'outputfileNormalEquation filename inputfileNormalEquation filename parameterSelection parameterSelectorType parameter order/selection of output normal equations outBlockSize uint block size for distributing the normal equations, 0: one block', 'display_text': 'Reorder inputfileNormalEquation by selecting parameters in a specific order. The parameterSelection also allows one to change dimension of the normal equations, either by cutting parameters or by inserting zero rows/columns for additional parameters. Without parameterSelection the order of parameters remains the same. Additionally the block sizes of the files can be adjusted. If outBlockSize is set to zero, the normal matrix is written to a single block file, which is needed by some programs.

    To eliminate parameters without changing the result of the other parameters use NormalsEliminate.'}, 'NormalsScale': { 'name': 'NormalsScale', 'key': 'NormalsScale', 'description': 'Scales rows and columns of a system of Scales rows and columns of a system of given by a diagonal matrix Scales rows and columns of a system of The estimated solution is now This is effectively the same as rescaling columns of the design matrix. This program is useful when combining normal equations from different sources, for example in case the units of certain parameters don\'t match.', 'config_table': 'outputfileNormalEquation filename inputfileNormalEquation filename inputfileFactorVector filename Vector containing the factors', 'display_text': 'Scales rows and columns of a system of inputfileNormalEquation given by a diagonal matrix inputfileFactorVector $\\M S$ \\[ \\bar{\\M N} := \\M S \\M N \\M S \\qquad\\text{and}\\qquad \\bar{\\M n} := \\M S \\M n. \\]The estimated solution is now \\[ \\bar{\\M x} := \\M S^{-1} \\M x. \\]This is effectively the same as rescaling columns of the design matrix. This program is useful when combining normal equations from different sources, for example in case the units of certain parameters don\'t match.'}, @@ -197,7 +197,7 @@ var documents = { 'PreprocessingGradiometer': { 'name': 'PreprocessingGradiometer', 'key': 'PreprocessingGradiometer', 'description': 'This program estimates empirical covariance functions of the gradiometer instrument noise and determine arc wise variances to downweight arcs with outliers. This program works similar to PreprocessingPod , see there for details. Here only the settings explained, which are different. ...', 'config_table': 'outputfileCovarianceFunction filename outputfileSigmasPerArc filename accuracies of each arc outputfileSggResiduals filename rightHandSide sggRightSideType input for the observation vector inputfileOrbit filename inputfileStarCamera filename earthRotation earthRotationType ephemerides ephemeridesType parametrizationBias parametrizationTemporalType per arc covarianceSgg sequence inputfileCovarianceFunction filename approximate covariances in time covarianceLength uint counts observation epochs sampling double [seconds] sampling of the covariance function iterationCount uint for the estimation of calibration parameter and error PSD', 'display_text': 'This program estimates empirical covariance functions of the gradiometer instrument noise and determine arc wise variances to downweight arcs with outliers. This program works similar to PreprocessingPod, see there for details. Here only the settings explained, which are different.

    ...'}, 'PreprocessingPod': { 'name': 'PreprocessingPod', 'key': 'PreprocessingPod', 'description': 'This program estimates empirical covariance functions of the instrument noise and determine arc wise variances to downweight arc with outliers. A complete least squares adjustment for gravity field determination is performed by computing the observation equations, see This program estimates empirical covariance functions of the instrument noise and determine arc wise variances to downweight arc with outliers. or This program estimates empirical covariance functions of the instrument noise and determine arc wise variances to downweight arc with outliers. for details. The normal equations are accumulated and solved to This program estimates empirical covariance functions of the instrument noise and determine arc wise variances to downweight arc with outliers. together with the estimated accuracies This program estimates empirical covariance functions of the instrument noise and determine arc wise variances to downweight arc with outliers. . The estimated residuals can be computed with computeResiduals . For each component (along, cross, radial) of the kinematic orbit positions a noise covariance function is estimated The covariance matrix is composed of the sum of matrices and unknown variance factors with the cosine transformation matrices An additional variance factor can be computed ( estimateArcSigmas ) for each arc according to where is the redundancy. This variance factor should be around one for normal behaving arcs as the noise characteristics is already considered by the covariance matrix but bad arcs get a much larger variance. By appling this factor bad arcs or arcs with large outliers are downweighted.', 'config_table': 'outputfileSolution filename estimated parameter vector (static part only) outputfileSigmax filename standard deviations of the parameters (sqrt of the diagonal of the inverse normal equation) outputfileParameterName filename names of estimated parameters (static part only) estimateArcSigmas sequence outputfileSigmasPerArcPod filename accuracies of each arc (POD2) estimateCovarianceFunctions sequence outputfileCovarianceFunctionPod filename covariance functions for along, cross, radial direction computeResiduals sequence outputfilePodResiduals filename observation choice obervation equations (POD) podIntegral sequence precise orbit data (integral approach) inputfileSatelliteModel filename satellite macro model rightHandSide podRightSideType input for the reduced observation vector inputfileOrbit filename used to evaluate the observation equations, not used as observations inputfileStarCamera filename earthRotation earthRotationType ephemerides ephemeridesType gradientfield gravityfieldType low order field to estimate the change of the gravity by position adjustement parametrizationGravity parametrizationGravityType gravity field parametrization parametrizationAcceleration parametrizationAccelerationType orbit force parameters keepSatelliteStates boolean set boundary values of each arc global integrationDegree uint integration of forces by polynomial approximation of degree n interpolationDegree uint orbit interpolation by polynomial approximation of degree n accelerateComputation boolean acceleration of computation by transforming the observations podVariational sequence precise orbit data (variational equations) rightHandSide sequence input for observation vectors inputfileOrbit filename kinematic positions as observations inputfileVariational filename approximate position and integrated state matrix ephemerides ephemeridesType parametrizationGravity parametrizationGravityType gravity field parametrization parametrizationAcceleration parametrizationAccelerationType orbit force parameters integrationDegree uint integration of forces by polynomial approximation of degree n interpolationDegree uint orbit interpolation by polynomial approximation of degree n accelerateComputation boolean acceleration of computation by transforming the observations covariancePod sequence sigma double apriori factor of covariance function inputfileSigmasPerArc filename apriori different accuaries for each arc (multiplicated with sigma) inputfileCovarianceFunction filename approximate covariances in time inputfileCovariancePodEpoch filename 3x3 epoch covariances sampling double [seconds] sampling of the covariance function inputfileArcList filename list to correspond points of time to arc numbers adjustmentThreshold double Adjustment factor threshold: Iteration will be stopped once both SST and POD adjustment factors are under this threshold iterationCount uint (maximum) number of iterations for the estimation of calibration parameter and error PSD', 'display_text': 'This program estimates empirical covariance functions of the instrument noise and determine arc wise variances to downweight arc with outliers.

    A complete least squares adjustment for gravity field determination is performed by computing the observation equations, see observation:podIntegral or observation:podVariational for details. The normal equations are accumulated and solved to outputfileSolution together with the estimated accuracies outputfileSigmax. The estimated residuals $\\hat{\\M e}=\\M l-\\M A\\hat{\\M x}$ can be computed with computeResiduals.

    For each component (along, cross, radial) of the kinematic orbit positions a noise covariance function is estimated \\[ \\text{cov}(\\Delta t_i) = \\sum_{n=0}^{N-1} a_n^2 \\cos\\left(\\frac{\\pi}{T} n\\Delta t_i\\right). \\]The covariance matrix is composed of the sum of matrices $F_n$ and unknown variance factors \\[ \\M\\Sigma = a_1^2\\M F_1 + a_2^2 \\M F_2 + \\cdots + a_N^2\\M F_N, \\]with the cosine transformation matrices \\[ \\M F_n = \\left(\\cos\\left(\\frac{\\pi}{T} n(t_i-t_k)\\right)\\right)_{ik}. \\] An additional variance factor can be computed (estimateArcSigmas) for each arc $k$ according to \\[ \\hat{\\sigma}_k^2 = \\frac{\\hat{\\M e}_k^T\\M\\Sigma^{-1}\\hat{\\M e}_k}{r_k}, \\]where $r_k$ is the redundancy. This variance factor should be around one for normal behaving arcs as the noise characteristics is already considered by the covariance matrix but bad arcs get a much larger variance. By appling this factor bad arcs or arcs with large outliers are downweighted.'}, 'PreprocessingSst': { 'name': 'PreprocessingSst', 'key': 'PreprocessingSst', 'description': 'This program processes satellite-to-satellite-tracking (SST) and kinematic orbit observations in a GRACE like configuration. Three different observation groups are considered separately: SST and POD1/POD2 for the two satellites. This program works similar to PreprocessingPod , see there for details. Here only deviations in the settings are explained. Precise orbit data (POD) often contains systematic errors in addition to stochastic noise. In this case the variance component estimation fails and assigns too much weight to the POD data. Therefore an additional downweightPod factor can be applied to the standard deviation of POD for the next least squares adjustment in the iteration. This factor should also applied as sigma in This program processes satellite-to-satellite-tracking (SST) and kinematic orbit observations in a GRACE like configuration. Three different observation groups are considered separately: SST and POD1/POD2 for the two satellites. This program works similar to for computation of the final solution e.g. with NormalsSolverVCE . Short time variations of the gravity field can be co-estimated together with the static/monthly mean gravity field. The short time parameters must also be set in This program processes satellite-to-satellite-tracking (SST) and kinematic orbit observations in a GRACE like configuration. Three different observation groups are considered separately: SST and POD1/POD2 for the two satellites. This program works similar to and can then be selected by This program processes satellite-to-satellite-tracking (SST) and kinematic orbit observations in a GRACE like configuration. Three different observation groups are considered separately: SST and POD1/POD2 for the two satellites. This program works similar to . If these parameters are not time variable, for example when a range of static parameters is selected, they are set up as constant for each time interval defined in inputfileArcList . The parameters are constrained by an This program processes satellite-to-satellite-tracking (SST) and kinematic orbit observations in a GRACE like configuration. Three different observation groups are considered separately: SST and POD1/POD2 for the two satellites. This program works similar to . The weight of the constrain equations in terms of the standard deviation can be estimated by means of Variance Component Estimation (VCE) if estimateShortTimeVariations:estimateSigma is set. The mathematical background of this co-estimation can be found in: Kvas, A., Mayer-Gürr, T. GRACE gravity field recovery with background model uncertainties. J Geod 93, 2543–2552 (2019). https://doi.org/10.1007/s00190-019-01314-1 .', 'config_table': 'outputfileSolution filename estimated parameter vector (static part only) outputfileSigmax filename standard deviations of the parameters (sqrt of the diagonal of the inverse normal equation) outputfileParameterName filename estimated signal parameters (index is appended) estimateArcSigmas sequence outputfileSigmasPerArcSst filename accuracies of each arc (SST) outputfileSigmasPerArcPod1 filename accuracies of each arc (POD1) outputfileSigmasPerArcPod2 filename accuracies of each arc (POD2) estimateEpochSigmas sequence outputfileSigmasPerEpochSst filename accuracies of each epoch (SST) outputfileSigmasPerEpochPod1 filename accuracies of each epoch (POD1) outputfileSigmasPerEpochPod2 filename accuracies of each epoch (POD2) estimateCovarianceFunctions sequence outputfileCovarianceFunctionSst filename covariance function outputfileCovarianceFunctionPod1 filename covariance functions for along, cross, radial direction outputfileCovarianceFunctionPod2 filename covariance functions for along, cross, radial direction estimateSstArcCovarianceSigmas sequence outputfileSigmasCovarianceMatrixArc filename one variance factor per matrix computeResiduals sequence outputfileSstResiduals filename outputfilePod1Residuals filename outputfilePod2Residuals filename observation choice obervation equations (Sst) sstIntegral sequence integral approach inputfileSatelliteModel1 filename satellite macro model inputfileSatelliteModel2 filename satellite macro model rightHandSide sstRightSideType input for the reduced observation vector sstType choice range rangeRate rangeAcceleration none inputfileOrbit1 filename used to evaluate the observation equations, not used as observations inputfileOrbit2 filename used to evaluate the observation equations, not used as observations inputfileStarCamera1 filename inputfileStarCamera2 filename earthRotation earthRotationType ephemerides ephemeridesType gradientfield gravityfieldType low order field to estimate the change of the gravity by position adjustement parametrizationGravity parametrizationGravityType gravity field parametrization parametrizationAcceleration1 parametrizationAccelerationType orbit1 force parameters parametrizationAcceleration2 parametrizationAccelerationType orbit2 force parameters parametrizationSst parametrizationSatelliteTrackingType satellite tracking parameter keepSatelliteStates boolean set boundary values of each arc global integrationDegree uint integration of forces by polynomial approximation of degree n interpolationDegree uint orbit interpolation by polynomial approximation of degree n sstVariational sequence variational equations rightHandSide sequence input for observation vectors inputfileSatelliteTracking filename ranging observations and corrections inputfileOrbit1 filename kinematic positions of satellite A as observations inputfileOrbit2 filename kinematic positions of satellite B as observations sstType choice range rangeRate none inputfileVariational1 filename approximate position and integrated state matrix inputfileVariational2 filename approximate position and integrated state matrix ephemerides ephemeridesType parametrizationGravity parametrizationGravityType gravity field parametrization parametrizationAcceleration1 parametrizationAccelerationType orbit1 force parameters parametrizationAcceleration2 parametrizationAccelerationType orbit2 force parameters parametrizationSst parametrizationSatelliteTrackingType satellite tracking parameter integrationDegree uint integration of forces by polynomial approximation of degree n interpolationDegree uint orbit interpolation by polynomial approximation of degree n covarianceSst sequence sigma double apriori factor of covariance function inputfileSigmasPerArc filename apriori different accuaries for each arc (multiplicated with sigma) inputfileSigmasPerEpoch filename apriori different accuaries for each epoch inputfileCovarianceFunction filename approximate covariances in time inputfileCovarianceMatrixArc filename Must be given per sst arc with correct dimensions. inputfileSigmasCovarianceMatrixArc filename Vector with one sigma for each sampling double [seconds] sampling of the covariance function covariancePod1 sequence sigma double apriori factor of covariance function inputfileSigmasPerArc filename apriori different accuaries for each arc (multiplicated with sigma) inputfileSigmasPerEpoch filename apriori different accuaries for each epoch inputfileCovarianceFunction filename approximate covariances in time inputfileCovariancePodEpoch filename 3x3 epoch covariances sampling double [seconds] sampling of the covariance function covariancePod2 sequence sigma double apriori factor of covariance function inputfileSigmasPerArc filename apriori different accuaries for each arc (multiplicated with sigma) inputfileSigmasPerEpoch filename apriori different accuaries for each epoch inputfileCovarianceFunction filename approximate covariances in time inputfileCovariancePodEpoch filename 3x3 epoch covariances sampling double [seconds] sampling of the covariance function estimateShortTimeVariations sequence co-estimate short time gravity field variations estimateSigma boolean estimate standard deviation via VCE autoregressiveModelSequence autoregressiveModelSequenceType AR model sequence for constraining short time gravity variations parameterSelection parameterSelectorType parameters describing the short time gravity field downweightPod double downweight factor for POD inputfileArcList filename list to correspond points of time to arc numbers iterationCount uint (maximum) number of iterations for the estimation of calibration parameter and error PSD variableNameIterations string All output fileNames in preprocessing iteration are expanded with this variable prior to writing to disk defaultBlockSize uint block size of static normal equation blocks', 'display_text': 'This program processes satellite-to-satellite-tracking (SST) and kinematic orbit observations in a GRACE like configuration. Three different observation groups are considered separately: SST and POD1/POD2 for the two satellites. This program works similar to PreprocessingPod, see there for details. Here only deviations in the settings are explained.

    Precise orbit data (POD) often contains systematic errors in addition to stochastic noise. In this case the variance component estimation fails and assigns too much weight to the POD data. Therefore an additional downweightPod factor can be applied to the standard deviation of POD for the next least squares adjustment in the iteration. This factor should also applied as sigma in observation for computation of the final solution e.g. with NormalsSolverVCE.

    Short time variations of the gravity field can be co-estimated together with the static/monthly mean gravity field. The short time parameters must also be set in observation:parametrizationGravity and can then be selected by estimateShortTimeVariations:parameterSelection. If these parameters are not time variable, for example when a range of static parameters is selected, they are set up as constant for each time interval defined in inputfileArcList. The parameters are constrained by an estimateShortTimeVariations:autoregressiveModelSequence. The weight of the constrain equations in terms of the standard deviation can be estimated by means of Variance Component Estimation (VCE) if estimateShortTimeVariations:estimateSigma is set. The mathematical background of this co-estimation can be found in:

    Kvas, A., Mayer-Gürr, T. GRACE gravity field recovery with background model uncertainties. J Geod 93, 2543–2552 (2019). https://doi.org/10.1007/s00190-019-01314-1.'}, -'PreprocessingVariationalEquation': { 'name': 'PreprocessingVariationalEquation', 'key': 'PreprocessingVariationalEquation', 'description': 'This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by . This means for each arc new initial state parameters are setup. In a first step the This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by acting on the satellite are evaluated at the apriori positions given by This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by . Non-conservative forces like solar radiation pressure needs the orientation of the satellite ( This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by ) and additional a satellite macro model ( satelliteModel ) with the surface properties. Furthermore This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by observations are also considered. In a second step the accelerations are integrated twice to an dynamic orbit unsing a moving polynomial with the degree integrationDegree . The orbit is corrected to be self-consistent. This means the forces should be evaluated at the new integrated positions instead of the apriori ones. This correction is computed in a linear approximation using the gradient of the forces with respect to the positions ( gradientfield ). As this term is small generally only the largest force components has to be considered. A low degree spherical harmonic expansion of the static gravity field (about up to degree 5) is sufficient in almost all cases. In this step also the state transition matrix (the partial derivatices of the current state, position and velocity) with respect to the initial state is computed. The integrated orbit together with the state transitions are stored in This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by , the integrated orbit only in This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by . To improve the numerical stability a reference ellipse can be reduced beforehand using Enke\'s method ( useEnke ). Mathematically the result is the same, but as the large central term is removed before and restored afterwards more digits are available for the computation. The integrated orbit should be fitted to observations afterwards by the programs PreprocessingVariationalEquationOrbitFit and/or PreprocessingVariationalEquationSstFit . They apply a least squares adjustment by estimating some satellite parameters (e.g. an accelerometer bias). If the fitted orbit is to far away from the original This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by the linearization may not be accurate enough. In this case PreprocessingVariationalEquation should be run again with the fitted orbit as This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by and introducing the estimatedParameters as additional forces.', 'config_table': 'outputfileVariational filename approximate position and integrated state matrix outputfileOrbit filename integrated orbit inputfileSatelliteModel filename satellite macro model inputfileOrbit filename approximate position, used to evaluate the force inputfileStarCamera filename rotation from body frame to CRF inputfileAccelerometer filename non-gravitational forces in satellite reference frame forces forcesType estimatedParameters sequence satellite parameters e.g. from orbit fit parametrizationAcceleration parametrizationAccelerationType orbit force parameters inputfileParameter filename estimated orbit force parameters earthRotation earthRotationType ephemerides ephemeridesType gradientfield gravityfieldType low order field to estimate the change of the gravity by position adjustement integrationDegree uint integration of forces by polynomial approximation of degree n useEnke sequence integrate differential forces to an elliptical reference trajectory GM double geocentric gravitational constant used for elliptical reference orbit', 'display_text': 'This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by inputfileOrbit. This means for each arc new initial state parameters are setup.

    In a first step the forces acting on the satellite are evaluated at the apriori positions given by inputfileOrbit. Non-conservative forces like solar radiation pressure needs the orientation of the satellite (inputfileStarCamera) and additional a satellite macro model (satelliteModel) with the surface properties. Furthermore inputfileAccelerometer observations are also considered.

    In a second step the accelerations are integrated twice to an dynamic orbit unsing a moving polynomial with the degree integrationDegree. The orbit is corrected to be self-consistent. This means the forces should be evaluated at the new integrated positions instead of the apriori ones. This correction is computed in a linear approximation using the gradient of the forces with respect to the positions (gradientfield). As this term is small generally only the largest force components has to be considered. A low degree spherical harmonic expansion of the static gravity field (about up to degree 5) is sufficient in almost all cases. In this step also the state transition matrix (the partial derivatices of the current state, position and velocity) with respect to the initial state is computed. The integrated orbit together with the state transitions are stored in outputfileVariational, the integrated orbit only in outputfileOrbit.

    To improve the numerical stability a reference ellipse can be reduced beforehand using Enke\'s method (useEnke). Mathematically the result is the same, but as the large central term is removed before and restored afterwards more digits are available for the computation.

    The integrated orbit should be fitted to observations afterwards by the programs PreprocessingVariationalEquationOrbitFit and/or PreprocessingVariationalEquationSstFit. They apply a least squares adjustment by estimating some satellite parameters (e.g. an accelerometer bias). If the fitted orbit is to far away from the original inputfileOrbit the linearization may not be accurate enough. In this case PreprocessingVariationalEquation should be run again with the fitted orbit as inputfileOrbit and introducing the estimatedParameters as additional forces.'}, +'PreprocessingVariationalEquation': { 'name': 'PreprocessingVariationalEquation', 'key': 'PreprocessingVariationalEquation', 'description': 'This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by . This means for each arc new initial state parameters are setup. In a first step the This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by acting on the satellite are evaluated at the apriori positions given by This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by . Non-conservative forces like solar radiation pressure needs the orientation of the satellite ( This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by ) and additional a satellite macro model ( satelliteModel ) with the surface properties. Furthermore This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by observations are also considered. In a second step the accelerations are integrated twice to an dynamic orbit using a moving polynomial with the degree integrationDegree . The orbit is corrected to be self-consistent. This means the forces should be evaluated at the new integrated positions instead of the apriori ones. This correction is computed in a linear approximation using the gradient of the forces with respect to the positions ( gradientfield ). As this term is small generally only the largest force components has to be considered. A low degree spherical harmonic expansion of the static gravity field (about up to degree 5) is sufficient in almost all cases. In this step also the state transition matrix (the partial derivatices of the current state, position and velocity) with respect to the initial state is computed. The integrated orbit together with the state transitions are stored in This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by , the integrated orbit only in This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by . To improve the numerical stability a reference ellipse can be reduced beforehand using Enke\'s method ( useEnke ). Mathematically the result is the same, but as the large central term is removed before and restored afterwards more digits are available for the computation. The integrated orbit should be fitted to observations afterwards by the programs PreprocessingVariationalEquationOrbitFit and/or PreprocessingVariationalEquationSstFit . They apply a least squares adjustment by estimating some satellite parameters (e.g. an accelerometer bias). If the fitted orbit is too far away from the original This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by the linearization may not be accurate enough. In this case PreprocessingVariationalEquation should be run again with the fitted orbit as This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by and introducing the estimatedParameters as additional forces.', 'config_table': 'outputfileVariational filename approximate position and integrated state matrix outputfileOrbit filename integrated orbit inputfileSatelliteModel filename satellite macro model inputfileOrbit filename approximate position, used to evaluate the force inputfileStarCamera filename rotation from body frame to CRF inputfileAccelerometer filename non-gravitational forces in satellite reference frame forces forcesType estimatedParameters sequence satellite parameters e.g. from orbit fit parametrizationAcceleration parametrizationAccelerationType orbit force parameters inputfileParameter filename estimated orbit force parameters earthRotation earthRotationType ephemerides ephemeridesType gradientfield gravityfieldType low order field to estimate the change of the gravity by position adjustement integrationDegree uint integration of forces by polynomial approximation of degree n useEnke sequence integrate differential forces to an elliptical reference trajectory GM double geocentric gravitational constant used for elliptical reference orbit', 'display_text': 'This program integrates an orbit dynamically using the given forces and setup the state transition matrix for each time step. These are the prerequisite for a least squares adjustement (e.g. gravity field determination) using the variational equation approach. The variational equations are computed arc wise as defined by inputfileOrbit. This means for each arc new initial state parameters are setup.

    In a first step the forces acting on the satellite are evaluated at the apriori positions given by inputfileOrbit. Non-conservative forces like solar radiation pressure needs the orientation of the satellite (inputfileStarCamera) and additional a satellite macro model (satelliteModel) with the surface properties. Furthermore inputfileAccelerometer observations are also considered.

    In a second step the accelerations are integrated twice to an dynamic orbit using a moving polynomial with the degree integrationDegree. The orbit is corrected to be self-consistent. This means the forces should be evaluated at the new integrated positions instead of the apriori ones. This correction is computed in a linear approximation using the gradient of the forces with respect to the positions (gradientfield). As this term is small generally only the largest force components has to be considered. A low degree spherical harmonic expansion of the static gravity field (about up to degree 5) is sufficient in almost all cases. In this step also the state transition matrix (the partial derivatices of the current state, position and velocity) with respect to the initial state is computed. The integrated orbit together with the state transitions are stored in outputfileVariational, the integrated orbit only in outputfileOrbit.

    To improve the numerical stability a reference ellipse can be reduced beforehand using Enke\'s method (useEnke). Mathematically the result is the same, but as the large central term is removed before and restored afterwards more digits are available for the computation.

    The integrated orbit should be fitted to observations afterwards by the programs PreprocessingVariationalEquationOrbitFit and/or PreprocessingVariationalEquationSstFit. They apply a least squares adjustment by estimating some satellite parameters (e.g. an accelerometer bias). If the fitted orbit is too far away from the original inputfileOrbit the linearization may not be accurate enough. In this case PreprocessingVariationalEquation should be run again with the fitted orbit as inputfileOrbit and introducing the estimatedParameters as additional forces.'}, 'PreprocessingVariationalEquationOrbitFit': { 'name': 'PreprocessingVariationalEquationOrbitFit', 'key': 'PreprocessingVariationalEquationOrbitFit', 'description': 'This program fits an This program fits an to an observed This program fits an by estimating parameters in a least squares adjustment. Additional to the initial satellite state for each arc, these parameters can be This program fits an , satellite This program fits an and stochastic pulses (velocity jumps) at given times, This program fits an . The estimated parameters can be stored with This program fits an and an extra file with the parameter names is created. The fitted orbit is written as new reference in This program fits an and additionally in This program fits an . The observed orbit positions ( This program fits an ) together with the epoch wise covariance matrix ( This program fits an ) must be splitted in the same arcs as the variational equations but not necessarily uniform distributed (use irregularData in InstrumentSynchronize ). An iterative downweighting of outliers is performed by M-Huber method. The observation equations (parameter sensitity matrix) are computed by integration of the variational equations ( This program fits an ) using a polynomial with integrationDegree and interpolated to the observation epochs using a polynomial with interpolationDegree . All parameters used here must be reestimated in the full least squares adjustment for the gravity field determination to get a solution which is not biased towards the reference field. The solution of additional estimations are relative (deltas) as the parameters are already used as Taylor point in the reference orbit. See also PreprocessingVariationalEquation .', 'config_table': 'outputfileVariational filename approximate position and integrated state matrix outputfileOrbit filename integrated orbit outputfileSolution filename estimated calibration and state parameters inputfileVariational filename approximate position and integrated state matrix inputfileOrbit filename kinematic positions of satellite as observations inputfileCovariancePodEpoch filename 3x3 epoch wise covariances ephemerides ephemeridesType may be needed by parametrizationAcceleration parametrizationGravity parametrizationGravityType gravity field parametrization parametrizationAcceleration parametrizationAccelerationType orbit force parameters stochasticPulse timeSeriesType integrationDegree uint integration of forces by polynomial approximation of degree n interpolationDegree uint orbit interpolation by polynomial approximation of degree n iterationCount uint for the estimation of calibration parameter and error PSD', 'display_text': 'This program fits an inputfileVariational to an observed inputfileOrbit by estimating parameters in a least squares adjustment. Additional to the initial satellite state for each arc, these parameters can be parametrizationGravity, satellite parametrizationAcceleration and stochastic pulses (velocity jumps) at given times, stochasticPulse. The estimated parameters can be stored with outputfileSolution and an extra file with the parameter names is created. The fitted orbit is written as new reference in outputfileVariational and additionally in outputfileOrbit.

    The observed orbit positions (inputfileOrbit) together with the epoch wise covariance matrix (inputfileCovariancePodEpoch) must be splitted in the same arcs as the variational equations but not necessarily uniform distributed (use irregularData in InstrumentSynchronize). An iterative downweighting of outliers is performed by M-Huber method.

    The observation equations (parameter sensitity matrix) are computed by integration of the variational equations (inputfileVariational) using a polynomial with integrationDegree and interpolated to the observation epochs using a polynomial with interpolationDegree.

    All parameters used here must be reestimated in the full least squares adjustment for the gravity field determination to get a solution which is not biased towards the reference field. The solution of additional estimations are relative (deltas) as the parameters are already used as Taylor point in the reference orbit.

    See also PreprocessingVariationalEquation.'}, 'PreprocessingVariationalEquationSstFit': { 'name': 'PreprocessingVariationalEquationSstFit', 'key': 'PreprocessingVariationalEquationSstFit', 'description': 'This program fits two This program fits two to satellite-to-satellite-tracking (SST) and orbit observations in a GRACE like configuration. It works similar to PreprocessingVariationalEquationOrbitFit , see there for details. As the relative weighting of the observation types is important complex description of the covariances can be set with This program fits two , This program fits two , This program fits two .', 'config_table': 'outputfileVariational1 filename approximate position and integrated state matrix outputfileVariational2 filename approximate position and integrated state matrix outputfileOrbit1 filename integrated orbit outputfileOrbit2 filename integrated orbit outputfileSolution1 filename estimated calibration and state parameters outputfileSolution2 filename estimated calibration and state parameters rightHandSide sequence input for observation vectors inputfileSatelliteTracking filename ranging observations and corrections inputfileOrbit1 filename kinematic positions of satellite A as observations inputfileOrbit2 filename kinematic positions of satellite B as observations sstType choice range rangeRate none inputfileVariational1 filename approximate position and integrated state matrix inputfileVariational2 filename approximate position and integrated state matrix ephemerides ephemeridesType parametrizationGravity parametrizationGravityType gravity field parametrization parametrizationAcceleration1 parametrizationAccelerationType orbit1 force parameters parametrizationAcceleration2 parametrizationAccelerationType orbit2 force parameters parametrizationSst parametrizationSatelliteTrackingType satellite tracking parameter integrationDegree uint integration of forces by polynomial approximation of degree n interpolationDegree uint orbit interpolation by polynomial approximation of degree n covarianceSst covarianceSstType covariance matrix of satellite to satellite tracking observations covariancePod1 covariancePodType covariance matrix of kinematic orbits (satellite 1) covariancePod2 covariancePodType covariance matrix of kinematic orbits (satellite 2) iterationCount uint for the estimation of calibration parameter and error PSD', 'display_text': 'This program fits two inputfileVariational1/2 to satellite-to-satellite-tracking (SST) and orbit observations in a GRACE like configuration. It works similar to PreprocessingVariationalEquationOrbitFit, see there for details.

    As the relative weighting of the observation types is important complex description of the covariances can be set with covarianceSst, covariancePod1, covariancePod2.'}, 'NoiseAccelerometer': { 'name': 'NoiseAccelerometer', 'key': 'NoiseAccelerometer', 'description': 'This program adds noise and biases to simulated accelerometer data generated by SimulateAccelerometer . See This program adds noise and biases to simulated for details on noise generation.', 'config_table': 'outputfileAccelerometer filename inputfileAccelerometer filename biasAlong double [m/s**2] biasCross double [m/s**2] biasRadial double [m/s**2] noiseAlong noiseGeneratorType [m/s**2] noiseCross noiseGeneratorType [m/s**2] noiseRadial noiseGeneratorType [m/s**2]', 'display_text': 'This program adds noise and biases to simulated accelerometer data generated by SimulateAccelerometer. See noiseGenerator for details on noise generation.'}, @@ -219,6 +219,7 @@ var documents = { 'SimulateStarCameraGrace': { 'name': 'SimulateStarCameraGrace', 'key': 'SimulateStarCameraGrace', 'description': 'Simulates star camera data of the two GRACE satellites. x: the antenna center pointing to the other satellite. y: normal to line of sight and the radial direction. z: forms a right handed system.', 'config_table': 'outputfileStarCamera1 filename outputfileStarCamera2 filename inputfileOrbit1 filename position define the orientation of the satellite at each epoch inputfileOrbit2 filename position define the orientation of the satellite at each epoch antennaCenters choice KBR antenna phase center value sequence center1X double x-coordinate of antenna position in SRF [m] for GRACEA center1Y double y-coordinate of antenna position in SRF [m] for GRACEA center1Z double z-coordinate of antenna position in SRF [m] for GRACEA center2X double x-coordinate of antenna position in SRF [m] for GRACEB center2Y double y-coordinate of antenna position in SRF [m] for GRACEB center2Z double z-coordinate of antenna position in SRF [m] for GRACEB file sequence inputAntennaCenters filename', 'display_text': 'Simulates star camera data of the two GRACE satellites.

    • x: the antenna center pointing to the other satellite.
    • y: normal to line of sight and the radial direction.
    • z: forms a right handed system.
    '}, 'SimulateStarCameraSentinel1': { 'name': 'SimulateStarCameraSentinel1', 'key': 'SimulateStarCameraSentinel1', 'description': 'This program simulates star camera measurements at each satellite\'s position for the Sentinel 1A satellite. The This program simulates must contain positions and velocities (see OrbitAddVelocityAndAcceleration ). The resulting rotation matrices rotate from satellite frame to inertial frame.', 'config_table': 'outputfileStarCamera filename inputfileOrbit filename position and velocity defines the orientation of the satellite at each epoch', 'display_text': 'This program simulates star camera measurements at each satellite\'s position for the Sentinel 1A satellite. The inputfileOrbit must contain positions and velocities (see OrbitAddVelocityAndAcceleration). The resulting rotation matrices rotate from satellite frame to inertial frame.'}, 'SimulateStarCameraTerrasar': { 'name': 'SimulateStarCameraTerrasar', 'key': 'SimulateStarCameraTerrasar', 'description': 'This program simulates This program simulates measurements at each satellite\'s position for the Terrasar satellite. The This program simulates must contain positions and velocities (see OrbitAddVelocityAndAcceleration ). The resulting rotation matrices rotate from satellite frame to inertial frame. H. Fiedler, E. Boerner, J. Mittermayer and G. Krieger, Total zero Doppler Steering-a new method for minimizing the Doppler centroid, in IEEE Geoscience and Remote Sensing Letters, vol. 2, no. 2, pp. 141-145, April 2005, https://www.doi.org/10.1109/LGRS.2005.844591 .', 'config_table': 'outputfileStarCamera filename rotation from satellite to inertial frame (x: along, y: cross, z: nadir) inputfileOrbit filename position and velocity defines the orientation of the satellite at each epoch', 'display_text': 'This program simulates outputfileStarCamera measurements at each satellite\'s position for the Terrasar satellite. The inputfileOrbit must contain positions and velocities (see OrbitAddVelocityAndAcceleration). The resulting rotation matrices rotate from satellite frame to inertial frame.

    H. Fiedler, E. Boerner, J. Mittermayer and G. Krieger, Total zero Doppler Steering-a new method for minimizing the Doppler centroid, in IEEE Geoscience and Remote Sensing Letters, vol. 2, no. 2, pp. 141-145, April 2005, https://www.doi.org/10.1109/LGRS.2005.844591.'}, +'SlrProcessing': { 'name': 'SlrProcessing', 'key': 'SlrProcessing', 'description': 'This program processes SLR normal point or full rate observations. It calculates the linearized observation equations, accumulates them into a system of normal equations and solves it. To calculate observation equations from the passes, the model parameters or unknown parameters need to be defined beforehand. These unknown parameters can be chosen arbitrarily by the user with an adequate list of defined This program processes SLR normal point or full rate observations. It calculates the linearized observation equations, accumulates them into a system of normal equations and solves it. . Some of the This program processes SLR normal point or full rate observations. It calculates the linearized observation equations, accumulates them into a system of normal equations and solves it. also include a priori models. Lastly it is required to define the process flow of the SLR processing. This is accomplished with a list of This program processes SLR normal point or full rate observations. It calculates the linearized observation equations, accumulates them into a system of normal equations and solves it. . Each step is processed consecutively. Some steps allow the selection of parameters, station, or satellites, which affects all subsequent steps. The This program processes SLR normal point or full rate observations. It calculates the linearized observation equations, accumulates them into a system of normal equations and solves it. is used to precompute Earth rotation and station displacements with a uniform sampling. In a second step these values are interpolated to the observation epochs. A sampling of about 10 minutes should be adequate. It should be noted that GROOPS uses GPS time format, but normal point/full rate data files and CPF files, provided by ILRS data centers are given in UTC time format.', 'config_table': 'timeSeries timeSeriesType defines station movements and earth rotation epochs satellite slrSatelliteGeneratorType satellites station slrStationGeneratorType ground station network earthRotation earthRotationType apriori earth rotation parametrization slrParametrizationType models and parameters processingStep slrProcessingStepType steps are processed consecutively', 'display_text': 'This program processes SLR normal point or full rate observations. It calculates the linearized observation equations, accumulates them into a system of normal equations and solves it.

    To calculate observation equations from the passes, the model parameters or unknown parameters need to be defined beforehand. These unknown parameters can be chosen arbitrarily by the user with an adequate list of defined parametrization. Some of the parametrization also include a priori models.

    Lastly it is required to define the process flow of the SLR processing. This is accomplished with a list of processingSteps. Each step is processed consecutively. Some steps allow the selection of parameters, station, or satellites, which affects all subsequent steps.

    The timeSeries is used to precompute Earth rotation and station displacements with a uniform sampling. In a second step these values are interpolated to the observation epochs. A sampling of about 10 minutes should be adequate.

    It should be noted that GROOPS uses GPS time format, but normal point/full rate data files and CPF files, provided by ILRS data centers are given in UTC time format.'}, 'FileConvert': { 'name': 'FileConvert', 'key': 'FileConvert', 'description': 'Converts GROOPS file between different file formats (ASCII, XML, binary), see file formats for details. It prints also some information about the content. Therefore it can be used to get an idea about the content of binary files.', 'config_table': 'outputfile filename GROOPS formats: .xml, .txt, .dat inputfile filename GROOPS formats: .xml, .txt, .dat', 'display_text': 'Converts GROOPS file between different file formats (ASCII, XML, binary), see file formats for details. It prints also some information about the content. Therefore it can be used to get an idea about the content of binary files.'}, 'FileCreateDirectories': { 'name': 'FileCreateDirectories', 'key': 'FileCreateDirectories', 'description': 'Creates the directory and parent directories as needed.', 'config_table': 'directory filename', 'display_text': 'Creates the directory and parent directories as needed.'}, 'FileMove': { 'name': 'FileMove', 'key': 'FileMove', 'description': 'Move/rename file or directory. If the outputfile is an existing directory the inputfile is moved into it.', 'config_table': 'outputfile filename target name or directory for the move/rename inputfile filename', 'display_text': 'Move/rename file or directory. If the outputfile is an existing directory the inputfile is moved into it.'}, @@ -232,6 +233,9 @@ var documents = { 'Champ2AccStar': { 'name': 'Champ2AccStar', 'key': 'Champ2AccStar', 'description': 'This program reads in CHAMP accelerometer and star camera data given in the special CHAMP format. In case of CHAMP accelerometer and star camera data is both stored in one file. A description of the format can be found under: http://op.gfz-potsdam.de/champ/docs_CHAMP/CH-GFZ-FD-001.pdf .', 'config_table': 'outputfileAccelerometer filename outputfileAngularAcceleration filename outputfileStarCamera filename inputfile filename', 'display_text': 'This program reads in CHAMP accelerometer and star camera data given in the special CHAMP format. In case of CHAMP accelerometer and star camera data is both stored in one file. A description of the format can be found under: http://op.gfz-potsdam.de/champ/docs_CHAMP/CH-GFZ-FD-001.pdf.'}, 'Champ2Orbit': { 'name': 'Champ2Orbit', 'key': 'Champ2Orbit', 'description': 'This program reads in CHAMP precise science orbits in the special CHORB format. A description of the format can be found under: http://op.gfz-potsdam.de/champ/docs_CHAMP/CH-GFZ-FD-002.pdf', 'config_table': 'outputfileOrbit filename earthRotation earthRotationType inputfile filename', 'display_text': 'This program reads in CHAMP precise science orbits in the special CHORB format. A description of the format can be found under: http://op.gfz-potsdam.de/champ/docs_CHAMP/CH-GFZ-FD-002.pdf'}, 'Cosmic2OrbitStar': { 'name': 'Cosmic2OrbitStar', 'key': 'Cosmic2OrbitStar', 'description': 'This program reads in cosmic orbit and star camera data given in the CHAMP format. In case of cosmic orbit and star camera data is stored in one file. A description of the format can be found under: http://op.gfz-potsdam.de/champ/docs_CHAMP/CH-GFZ-FD-001.pdf', 'config_table': 'outputfileOrbit filename outputfileStarCamera filename inputfile filename', 'display_text': 'This program reads in cosmic orbit and star camera data given in the CHAMP format. In case of cosmic orbit and star camera data is stored in one file. A description of the format can be found under: http://op.gfz-potsdam.de/champ/docs_CHAMP/CH-GFZ-FD-001.pdf'}, +'Cpf2Orbit': { 'name': 'Cpf2Orbit', 'key': 'Cpf2Orbit', 'description': 'Converts and writes an instrument file (ORBIT) . The time format of the CPF file is UTC. The coordinate system used in the CPF format is usually represented in TRF. If Converts is provided the data are transformed from terrestrial (TRF) to celestial reference frame (CRF). See also Orbit2Cpf', 'config_table': 'outputfileOrbit filename earthRotation earthRotationType inputfile filename SLR CPF file', 'display_text': 'Converts CPF file and writes an instrument file (ORBIT).

    The time format of the CPF file is UTC. The coordinate system used in the CPF format is usually represented in TRF. If earthRotation is provided the data are transformed from terrestrial (TRF) to celestial reference frame (CRF).

    See also Orbit2Cpf'}, +'Crd2NormalPoints': { 'name': 'Crd2NormalPoints', 'key': 'Crd2NormalPoints', 'description': 'Converts and writes an instrument file (METEOROLOGICAL) including meteorological data like temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) including normal point data like range, accuracy, redundancy, wavelength and window size.', 'config_table': 'outputfileNormalPoints filename variable {station} available outputfileMeteorological filename variable {station} available inputfileSlrData filename SLR CRD files', 'display_text': 'Converts CRD file and writes an instrument file (METEOROLOGICAL) including meteorological data like temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) including normal point data like range, accuracy, redundancy, wavelength and window size.'}, +'Cstg2NormalPoints': { 'name': 'Cstg2NormalPoints', 'key': 'Cstg2NormalPoints', 'description': 'Converts provided by the and writes an instrument file (METEOROLOGICAL) including meteorological data like temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) including normal point data like range, accuracy, redundancy, wavelength and window size.', 'config_table': 'outputfileNormalPoints filename variable {station} available outputfileMeteorological filename variable {station} available inputfileSlrData filename SLR CSTG file', 'display_text': 'Converts CSTG file provided by the ILRS and writes an instrument file (METEOROLOGICAL) including meteorological data like temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) including normal point data like range, accuracy, redundancy, wavelength and window size.'}, 'DoodsonAdmittance2SupplementaryFiles': { 'name': 'DoodsonAdmittance2SupplementaryFiles', 'key': 'DoodsonAdmittance2SupplementaryFiles', 'description': 'The publication of an ocean tide model includes not only the atlas in the form of spherical harmonics coefficients, but also the matrix of Doodson multipliers ( outputfileDoodsonMatrix ) and the outputfileAdmittanceMatrix . The outputfileMajorTideList contains the fileNames for each contituent. The required information is taken from the The publication of an ocean tide model includes not only the atlas in the form of spherical harmonics coefficients, but also the matrix of Doodson multipliers ( . See also DoodsonHarmonics2PotentialCoefficients .', 'config_table': 'outputfileMajorTideList filename fileNames filename template for fileList, variables: doodson, name, cossin outputfileDoodsonMatrix filename outputfileAdmittanceMatrix filename inputfileAdmittance filename interpolation of minor constituents', 'display_text': 'The publication of an ocean tide model includes not only the atlas in the form of spherical harmonics coefficients, but also the matrix of Doodson multipliers (outputfileDoodsonMatrix) and the outputfileAdmittanceMatrix.

    The outputfileMajorTideList contains the fileNames for each contituent. The required information is taken from the inputfileAdmittance.

    See also DoodsonHarmonics2PotentialCoefficients.'}, 'DoodsonHarmonics2IersPotential': { 'name': 'DoodsonHarmonics2IersPotential', 'key': 'DoodsonHarmonics2IersPotential', 'description': 'Convert doodson harmonics to IERS conventions according to FES2004. cf. ftp://tai.bipm.org/iers/conv2010/chapter6/tidemodels/fes2004.dat .', 'config_table': 'outputfile filename according to IERS2010, chapter 6.3.2, footnote 7 inputfileDoodsonHarmoncis filename header string info for output header factor double minDegree uint maxDegree uint', 'display_text': 'Convert doodson harmonics to IERS conventions according to FES2004. cf. ftp://tai.bipm.org/iers/conv2010/chapter6/tidemodels/fes2004.dat.'}, 'DoodsonHarmonics2IersWaterHeight': { 'name': 'DoodsonHarmonics2IersWaterHeight', 'key': 'DoodsonHarmonics2IersWaterHeight', 'description': 'Convert doodson harmonics to IERS conventions according to FES2004. cf. ftp://tai.bipm.org/iers/conv2010/chapter6/tidemodels/fes2004.dat .', 'config_table': 'outputfile filename according to IERS2010, chapter 6.3.2, footnote 7 inputfileDoodsonHarmoncis filename inputfileTideGeneratingPotential filename to compute Xi phase correction header string info for output header kernel kernelType data type of output values factor double e.g. from [m] to [cm] minDegree uint maxDegree uint', 'display_text': 'Convert doodson harmonics to IERS conventions according to FES2004. cf. ftp://tai.bipm.org/iers/conv2010/chapter6/tidemodels/fes2004.dat.'}, @@ -297,10 +301,13 @@ var documents = { 'Igs2EarthOrientationParameter': { 'name': 'Igs2EarthOrientationParameter', 'key': 'Igs2EarthOrientationParameter', 'description': 'Read Rapid Earth Orientation Parameter from IGS daily file and write it as Read Rapid Earth Orientation Parameter from IGS daily file and write it as .', 'config_table': 'outputfileEOP filename inputfile filename timeStart time timeEnd time', 'display_text': 'Read Rapid Earth Orientation Parameter from IGS daily file and write it as outputfileEOP.'}, 'Jason2Starcamera': { 'name': 'Jason2Starcamera', 'key': 'Jason2Starcamera', 'description': 'This program reads in Jason star camera data given in a special format. Files available at: cddis.gsfc.nasa.gov/pub/doris/ancillary/quaternions/ja2/ . A description of the format can be found under: ftp://ftp.ids-doris.org/pub/ids/ancillary/quaternions/jason1_2_quaternion_solar_panel.pdf', 'config_table': 'outputfileStarCamera filename jasonNumber uint Jason number (different file format), 1 for Sentinel inputfile filename', 'display_text': 'This program reads in Jason star camera data given in a special format. Files available at: cddis.gsfc.nasa.gov/pub/doris/ancillary/quaternions/ja2/. A description of the format can be found under: ftp://ftp.ids-doris.org/pub/ids/ancillary/quaternions/jason1_2_quaternion_solar_panel.pdf'}, 'JplAscii2Ephemerides': { 'name': 'JplAscii2Ephemerides', 'key': 'JplAscii2Ephemerides', 'description': 'Read JPL DExxx (ASCII) ephemerides.', 'config_table': 'outputfileEphemerides filename inputfileHeader filename inputfileData filename', 'display_text': 'Read JPL DExxx (ASCII) ephemerides.'}, +'Merit2FullRate': { 'name': 'Merit2FullRate', 'key': 'Merit2FullRate', 'description': 'Converts and writes an instrument file (METEOROLOGICAL) including meteorological data like temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) including full rate data like range, accuracy, wavelength, azimuth and elevation.', 'config_table': 'outputfileNormalPoints filename variable {station} available outputfileMeteorological filename variable {station} available inputfileSlrData filename SLR MERIT II file', 'display_text': 'Converts MERIT II file and writes an instrument file (METEOROLOGICAL) including meteorological data like temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) including full rate data like range, accuracy, wavelength, azimuth and elevation.'}, +'Merit2NormalPoints': { 'name': 'Merit2NormalPoints', 'key': 'Merit2NormalPoints', 'description': 'Converts and writes an instrument file (METEOROLOGICAL) including meteorological data like temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) including normal point data like range, accuracy, redundancy, wavelength, window size, azimuth and elevation.', 'config_table': 'outputfileNormalPoints filename variable {station} available outputfileMeteorological filename variable {station} available inputfileSlrData filename SLR MERIT II file', 'display_text': 'Converts MERIT II file and writes an instrument file (METEOROLOGICAL) including meteorological data like temperature, air pressure and humidity as well as an instrument file (SATELLITELASERRANGING) including normal point data like range, accuracy, redundancy, wavelength, window size, azimuth and elevation.'}, 'NetCdf2GriddedData': { 'name': 'NetCdf2GriddedData', 'key': 'NetCdf2GriddedData', 'description': 'This program converts a COARDS compliant NetCDF file into an This program converts a COARDS compliant NetCDF file into an . If no specific input variableNameData are selected all suitable data are used. If the NETCDF file contains a time axis ( variableNameData ) an specific epoch can be selected with time . The nearest epoch in file is used. See also NetCdfInfo , GriddedData2NetCdf , NetCdf2GriddedDataTimeSeries .', 'config_table': 'outputfileGriddedData filename inputfileNetCdf filename variableNameLongitude string name of NetCDF variable variableNameLatitude string name of NetCDF variable variableNameTime string if with time axis: name of NetCDF variable variableNameData string data variables, otherwise all suitable data are used time time if with time axis: nearest epoch is used R double reference radius for ellipsoidal coordinates inverseFlattening double reference flattening for ellipsoidal coordinates', 'display_text': 'This program converts a COARDS compliant NetCDF file into an outputfileGriddedData. If no specific input variableNameData are selected all suitable data are used.

    If the NETCDF file contains a time axis (variableNameData) an specific epoch can be selected with time. The nearest epoch in file is used.

    See also NetCdfInfo, GriddedData2NetCdf, NetCdf2GriddedDataTimeSeries.'}, 'NetCdf2GriddedDataTimeSeries': { 'name': 'NetCdf2GriddedDataTimeSeries', 'key': 'NetCdf2GriddedDataTimeSeries', 'description': 'This program converts a COARDS compliant NetCDF file into This program converts a COARDS compliant NetCDF file into . If no specific input variableNameData are selected all suitable data are used. See also NetCdfInfo , NetCdf2GriddedData , GriddedDataTimeSeries2NetCdf .', 'config_table': 'outputfileGriddedDataTimeSeries filename inputfileNetCdf filename variableNameLongitude string name of NetCDF variable variableNameLatitude string name of NetCDF variable variableNameTime string name of NetCDF variable) variableNameData string data variables, otherwise all suitable data are used R double reference radius for ellipsoidal coordinates inverseFlattening double reference flattening for ellipsoidal coordinates', 'display_text': 'This program converts a COARDS compliant NetCDF file into outputfileGriddedDataTimeSeries. If no specific input variableNameData are selected all suitable data are used.

    See also NetCdfInfo, NetCdf2GriddedData, GriddedDataTimeSeries2NetCdf.'}, 'NetCdfInfo': { 'name': 'NetCdfInfo', 'key': 'NetCdfInfo', 'description': 'Print content information of a NetCDF file like dimensions, variables and attributes. See also NetCdf2GriddedData , NetCdf2GriddedDataTimeSeries , GriddedData2NetCdf , GriddedDataTimeSeries2NetCdf .', 'config_table': 'inputfileNetCdf filename', 'display_text': 'Print content information of a NetCDF file like dimensions, variables and attributes.

    See also NetCdf2GriddedData, NetCdf2GriddedDataTimeSeries, GriddedData2NetCdf, GriddedDataTimeSeries2NetCdf.'}, 'NormalsSphericalHarmonics2Sinex': { 'name': 'NormalsSphericalHarmonics2Sinex', 'key': 'NormalsSphericalHarmonics2Sinex', 'description': 'Write potential coefficients and normal equations to . See also Sinex2Normals and GnssNormals2Sinex .', 'config_table': 'outputfileSinex filename solutions in SINEX format inputfileNormals filename normal equation matrix inputfileSolution filename parameter vector inputfileSigmax filename standard deviations of the parameters (sqrt of the diagonal of the inverse normal equation) inputfileApriori filename apriori parameter vector inputfileAprioriMatrix filename normal equation matrix of applied constraints time time reference time for parameters sinexHeader sequence agencyCode string identify the agency providing the data timeStart time start time of the data timeEnd time end time of the data observationCode string technique used to generate the SINEX solution constraintCode string 0: tight constraint, 1: siginficant constraint, 2: unconstrained solutionContent string solution types contained in the SINEX solution (S O E T C A) description string organizitions gathering/alerting the file contents contact string Address of the relevant contact. e-mail output string Description of the file contents input string Brief description of the input used to generate this solution software string Software used to generate the file hardware string Computer hardware on which above software was run inputfileComment filename comments in the comment block from a file (truncated at 80 characters) comment string comments in the comment block', 'display_text': 'Write potential coefficients and normal equations to SINEX format.

    See also Sinex2Normals and GnssNormals2Sinex.'}, +'Orbit2Cpf': { 'name': 'Orbit2Cpf', 'key': 'Orbit2Cpf', 'description': 'Writes groops orbits to . The coordinate system used in the CPF format is usually presented in ITRF. The required time format for the input orbit file is GPS. The time format of the output CPF file is given in UTC. See also Cpf2Orbit .', 'config_table': 'outputfile filename inputfileOrbit filename inputfileSatelliteInfo filename Platform File earthRotation earthRotationType versionNumber uint Version number of production day with zero leading fill, e.g. 01 targetClass uint set 1 for passive retroreflector, set 0 for no retroreflector (includes debris)', 'display_text': 'Writes groops orbits to CPF file.

    The coordinate system used in the CPF format is usually presented in ITRF. The required time format for the input orbit file is GPS. The time format of the output CPF file is given in UTC.

    See also Cpf2Orbit.'}, 'Orbit2GroopsAscii': { 'name': 'Orbit2GroopsAscii', 'key': 'Orbit2GroopsAscii', 'description': 'Convert groops orbits and corresponding covariance information to ASCII format. The format is used to publish TUG orbits. It contains a two line header with a short description of the orbit defined in firstLine . The orbit is rotated to the Earth fixed frame (TRF) with Convert groops orbits and corresponding covariance information to ASCII format. The format is used to publish TUG orbits. It contains a two line header with a short description of the orbit defined in and given as one line per epoch. The epoch lines contained time [MJD GPS time], position x, y and z [m], and the epoch covariance xx, yy, zz, xy, xz and yz [ ]. See also GroopsAscii2Orbit .', 'config_table': 'outputfile filename inputfileOrbit filename inputfileCovariance filename earthRotation earthRotationType firstLine string Text for first line', 'display_text': 'Convert groops orbits and corresponding covariance information to ASCII format. The format is used to publish TUG orbits. It contains a two line header with a short description of the orbit defined in firstLine. The orbit is rotated to the Earth fixed frame (TRF) with earthRotation and given as one line per epoch. The epoch lines contained time [MJD GPS time], position x, y and z [m], and the epoch covariance xx, yy, zz, xy, xz and yz [$m^2$].

    See also GroopsAscii2Orbit.'}, 'Orbit2Sp3Format': { 'name': 'Orbit2Sp3Format', 'key': 'Orbit2Sp3Format', 'description': 'Writes orbits to . SP3 orbits are usually given in the terrestrial reference frame (TRF), so providing Writes orbits to automatically rotates the orbits from the celestial reference frame (CRF) to the TRF. Since SP3 orbits often use the center of Earth as a reference, a correction from center of mass to center of Earth can be applied to the orbits by providing Writes orbits to (e.g. ocean tides). See also Sp3Format2Orbit .', 'config_table': 'outputfile filename satellite sequence inputfileOrbit filename inputfileClock filename inputfileCovariance filename identifier string 3 characters (e.g. GNSS PRN: G01) orbitAccuracy double [m] used for accuracy codes in header (0 = unknown) earthRotation earthRotationType rotate data into Earth-fixed frame gravityfield gravityfieldType degree 1 fluid mantle for CM2CE correction (SP3 orbits should be in center of Earth) comment string comment lines (77 char max) firstLine string Text for first line e.g: u+U IGb14 KIN ITSG writeVelocity boolean write velocity in addition to position useSp3kFormat boolean use the extended sp3k format', 'display_text': 'Writes orbits to SP3 format.

    SP3 orbits are usually given in the terrestrial reference frame (TRF), so providing earthRotation automatically rotates the orbits from the celestial reference frame (CRF) to the TRF. Since SP3 orbits often use the center of Earth as a reference, a correction from center of mass to center of Earth can be applied to the orbits by providing gravityfield (e.g. ocean tides).

    See also Sp3Format2Orbit.'}, 'PotentialCoefficients2Icgem': { 'name': 'PotentialCoefficients2Icgem', 'key': 'PotentialCoefficients2Icgem', 'description': 'Write spherical harmonics in ICGEM format. GROOPS uses this format as default but this program enables the possibility to include comments and set the modelname.', 'config_table': 'outputfile filename inputfilePotentialCoefficients filename inputfileTrend filename oscillation sequence inputfileCosPotentialCoefficients filename inputfileSinPotentialCoefficients filename period string period of oscillation [year] comment string comment in header inputfileComment filename file containing comments for header modelname string name of the model tideSystem choice tide system of model zero_tide tide_free minDegree uint maxDegree uint GM double Geocentric gravitational constant R double reference radius time time reference time', 'display_text': 'Write spherical harmonics in ICGEM format. GROOPS uses this format as default but this program enables the possibility to include comments and set the modelname.'}, @@ -312,8 +319,11 @@ var documents = { 'Sinex2Normals': { 'name': 'Sinex2Normals', 'key': 'Sinex2Normals', 'description': 'Convert normal equations from to normal equations . See also GnssNormals2Sinex and NormalsSphericalHarmonics2Sinex .', 'config_table': 'outputfileNormals filename N, n: unconstrained normal equations outputfileNormalsConstraint filename N0, n0: normal equations of applied constraints outputfileSolution filename x: parameter vector outputfileSolutionApriori filename x0: a priori parameter vector inputFileSinex filename', 'display_text': 'Convert normal equations from SINEX format to normal equations.

    See also GnssNormals2Sinex and NormalsSphericalHarmonics2Sinex.'}, 'Sinex2StationDiscontinuities': { 'name': 'Sinex2StationDiscontinuities', 'key': 'Sinex2StationDiscontinuities', 'description': 'Convert station discontinuities from (e.g. ITRF20) to Convert station discontinuities from (MISCVALUE). A value of 1 means position discontinuity, a value of 2 means velocity discontinuity. Start and end epochs with value 0 are added in addition to the discontinuities from SINEX to define continuity interval borders. See also Sinex2StationPosition and Sinex2StationPostSeismicDeformation .', 'config_table': 'outputfileInstrument filename loop variable is replaced with station name (e.g. wtzz) inputfileDiscontinuities filename SINEX (e.g. ITRF20) station discontinuities variableLoopStation string variable name for station loop stationName string only export these stations', 'display_text': 'Convert station discontinuities from SINEX format (e.g. ITRF20) to outputfileInstrument (MISCVALUE). A value of 1 means position discontinuity, a value of 2 means velocity discontinuity. Start and end epochs with value 0 are added in addition to the discontinuities from SINEX to define continuity interval borders.

    See also Sinex2StationPosition and Sinex2StationPostSeismicDeformation.'}, 'Sinex2StationPositions': { 'name': 'Sinex2StationPositions', 'key': 'Sinex2StationPositions', 'description': 'Extracts station positions from inputfileSinexSolution ( ) and writes an Extracts station positions from of type VECTOR3D for each station. Positions will be computed at Extracts station positions from based on position and velocity of each provided interval in the SINEX file. With inputfileSinexDiscontinuities the bounds of these time spans are adjusted to the exact epochs of discontinuities. The inputfileSinexPostSeismicDeformations adds the ITRF post-seismic deformation model to the affected stations. The inputfileSinexFrequencies adds annual and semi-annual frequencies. If extrapolateBackward or extrapolateForward are provided, positions will also be computed for epochs before the first interval/after the last interval, based on the position and velocity of the first/last interval. Position extrapolation will stop at the first discontinuity before the first interval/after the last interval. Stations can be limited via stationName , otherwise all stations in inputfileSinexSolution will be used.', 'config_table': 'outputfileInstrument filename loop variable is replaced with station name (e.g. wtzz) variableLoopStation string variable name for station loop inputfileSinexSolution filename SINEX file inputfileSinexDiscontinuities filename SINEX file inputfileSinexPostSeismicDeformations filename SINEX file inputfileSinexFrequencies filename SINEX file (XYZ or ENU) timeSeries timeSeriesType compute positions for these epochs based on velocity extrapolateForward boolean also compute positions for epochs after last interval defined in SINEX file extrapolateBackward boolean also compute positions for epochs before first interval defined in SINEX file stationName string convert only these stations', 'display_text': 'Extracts station positions from inputfileSinexSolution (SINEX format description) and writes an outputfileInstrument of type VECTOR3D for each station. Positions will be computed at timeSeries based on position and velocity of each provided interval in the SINEX file. With inputfileSinexDiscontinuities the bounds of these time spans are adjusted to the exact epochs of discontinuities. The inputfileSinexPostSeismicDeformations adds the ITRF post-seismic deformation model to the affected stations. The inputfileSinexFrequencies adds annual and semi-annual frequencies.

    If extrapolateBackward or extrapolateForward are provided, positions will also be computed for epochs before the first interval/after the last interval, based on the position and velocity of the first/last interval. Position extrapolation will stop at the first discontinuity before the first interval/after the last interval.

    Stations can be limited via stationName, otherwise all stations in inputfileSinexSolution will be used.'}, +'SinexEccentricties2SlrPlatform': { 'name': 'SinexEccentricties2SlrPlatform', 'key': 'SinexEccentricties2SlrPlatform', 'description': 'Reads metadata like station name, station number, approximate station position and station eccentricities from (une version) and write them to the Reads metadata like station name, station number, approximate station position and station eccentricities from for each station.', 'config_table': 'outputfileStationInfo filename loop variable is replaced with station name variableLoopStation string variable name for station loop inputfileSinex filename SINEX file (.snx or .ssc) stationName string convert only these stations', 'display_text': 'Reads metadata like station name, station number, approximate station position and station eccentricities from Station Eccentricities Sinex File (une version) and write them to the outputfileStationInfo for each station.'}, 'SinexMetadata2GlonassFrequencyNumber': { 'name': 'SinexMetadata2GlonassFrequencyNumber', 'key': 'SinexMetadata2GlonassFrequencyNumber', 'description': 'Create Create matrix from with the columns: GLONASS PRN, SVN, mjdStart, mjdEnd, frequencyNumber. See also RinexObservation2GnssReceiver .', 'config_table': 'outputfileMatrixPrn2FrequencyNumber filename GROOPS matrix with columns: GLONASS PRN, SVN, mjdStart, mjdEnd, frequencyNumber inputfileSinexMetadata filename IGS SINEX metadata file', 'display_text': 'Create outputfileMatrixPrn2FrequencyNumber matrix from IGS SINEX metadata format with the columns: GLONASS PRN, SVN, mjdStart, mjdEnd, frequencyNumber.

    See also RinexObservation2GnssReceiver.'}, 'SinexMetadata2SatelliteModel': { 'name': 'SinexMetadata2SatelliteModel', 'key': 'SinexMetadata2SatelliteModel', 'description': 'Create Create from . If Create is provided it is used as a basis and values are updated from the metadata file. See also SatelliteModelCreate .', 'config_table': 'outputfileSatelliteModel filename inputfileSinexMetadata filename IGS SINEX metadata file inputfileSatelliteModel filename base satellite model svn string e.g. G040, R736, E204, C211', 'display_text': 'Create outputfileSatelliteModel from IGS SINEX metadata format.

    If inputfileSatelliteModel is provided it is used as a basis and values are updated from the metadata file.

    See also SatelliteModelCreate.'}, +'SlrComModel2RangeBiasStationSatellite': { 'name': 'SlrComModel2RangeBiasStationSatellite', 'key': 'SlrComModel2RangeBiasStationSatellite', 'description': 'Converts the tables of CoM corrections of José Rodríguez ( https://icts-yebes.oan.es/slr/com_models/models/ ) into station/satellite specific Converts the tables of CoM corrections of José Rodríguez ( . Only the deviations to the default value in Converts the tables of CoM corrections of José Rodríguez ( are written. This program must be called for every provided satellite. The range bias values can be used in Converts the tables of CoM corrections of José Rodríguez ( in SlrProcessing . Reference: Rodriguez J., Otsubo T., Appleby G. Upgraded Modelling for the Determination of Centre of Mass Corrections of Geodetic SLR Satellites: Impact on Key Parameters of the Terrestrial Reference Frame. Journal of Geodesy, 2019. doi: 10.1007/s00190-019-01315-0', 'config_table': 'outputfileRangeBias filename MISCVALUE, variable {station} available inputfileSatelliteInfo filename inputfile filename from Rodriguez model variableLoopStation string variable name for station loop stationName string convert only these stations', 'display_text': 'Converts the tables of CoM corrections of José Rodríguez (https://icts-yebes.oan.es/slr/com_models/models/) into station/satellite specific outputfileRangeBias. Only the deviations to the default value in inputfileSatelliteInfo are written. This program must be called for every provided satellite. The range bias values can be used in parametrization:rangeBiasStationSatelliteApriori in SlrProcessing.

    Reference: Rodriguez J., Otsubo T., Appleby G. Upgraded Modelling for the Determination of Centre of Mass Corrections of Geodetic SLR Satellites: Impact on Key Parameters of the Terrestrial Reference Frame. Journal of Geodesy, 2019. doi: 10.1007/s00190-019-01315-0'}, +'SlrSinexDataHandling2Files': { 'name': 'SlrSinexDataHandling2Files', 'key': 'SlrSinexDataHandling2Files', 'description': 'Converts SLR range and time bias from ILRS_Data_Handling_File_xxxx.xx.xx.snx provided at https://cddis.nasa.gov/archive/slr/products/resource/ . The range and time bias values can be used in Converts SLR range and time bias from in SlrProcessing .', 'config_table': 'outputfileRangeBiasStation filename MISCVALUE [m] outputfileRangeBiasStationSatellite filename MISCVALUE [m] outputfileTimeBias filename MISCVALUES(bias [s], drift [s/d]) variableLoopStation string variable name for station loop variableLoopSatellite string variable name for satellite loop inputfileSinex filename SINEX file (.snx) inputfileSatelliteId filename table SP3 and satellite name stationName string convert only these stations', 'display_text': 'Converts SLR range and time bias from ILRS_Data_Handling_File_xxxx.xx.xx.snx provided at https://cddis.nasa.gov/archive/slr/products/resource/. The range and time bias values can be used in parametrization:rangeBiasXxxApriori in SlrProcessing.'}, 'Sp3Format2Orbit': { 'name': 'Sp3Format2Orbit', 'key': 'Sp3Format2Orbit', 'description': 'Read orbits from and write an instrument file (ORBIT) . The additional outputfileClock is an instrument file (MISCVALUE) and outputfileCovariance is an instrument file (COVARIANCE3D) . With satelliteIdentifier a single satellite can be selected if the inputfile s contain more than one satellites. If satelliteIdentifier is empty the first satellite is taken. All satellites can be selected with satelliteIdentifier = <all> . In this case the identifier is appended to each output file. If Read orbits from is provided the data are transformed from terrestrial (TRF) to celestial reference frame (CRF). Since SP3 orbits often use the center of Earth as a reference, a correction from center of Earth to center of mass can be applied to the orbits by providing Read orbits from (e.g. ocean tides). See also Orbit2Sp3Format .', 'config_table': 'outputfileOrbit filename outputfileClock filename outputfileCovariance filename 3x3 epoch covariance satelliteIdentifier string e.g. L09 for GRACE A, empty: take first satellite, : identifier is appended to each file earthRotation earthRotationType rotation from TRF to CRF gravityfield gravityfieldType degree 1 fluid mantle for CM2CE correction (SP3 orbits should be in center of Earth) inputfile filename orbits in SP3 format', 'display_text': 'Read orbits from SP3 format and write an instrument file (ORBIT). The additional outputfileClock is an instrument file (MISCVALUE) and outputfileCovariance is an instrument file (COVARIANCE3D).

    With satelliteIdentifier a single satellite can be selected if the inputfiles contain more than one satellites. If satelliteIdentifier is empty the first satellite is taken. All satellites can be selected with satelliteIdentifier=<all>. In this case the identifier is appended to each output file.

    If earthRotation is provided the data are transformed from terrestrial (TRF) to celestial reference frame (CRF). Since SP3 orbits often use the center of Earth as a reference, a correction from center of Earth to center of mass can be applied to the orbits by providing gravityfield (e.g. ocean tides).

    See also Orbit2Sp3Format.'}, 'Swarm2Starcamera': { 'name': 'Swarm2Starcamera', 'key': 'Swarm2Starcamera', 'description': 'This program reads SWARM star camera data given in the cdf format and before converted to an ascii file using the program cdfexport provided by the Goddard Space Flight Center ( http://cdf.gsfc.nasa.gov/ ).', 'config_table': 'outputfileStarCamera filename earthRotation earthRotationType inputfile filename', 'display_text': 'This program reads SWARM star camera data given in the cdf format and before converted to an ascii file using the program cdfexport provided by the Goddard Space Flight Center (http://cdf.gsfc.nasa.gov/).'}, 'TerraSarTandem2Orbit': { 'name': 'TerraSarTandem2Orbit', 'key': 'TerraSarTandem2Orbit', 'description': 'This program reads in TerraSar-X or Tandem-X orbits in the special CHORB format and takes the appropriate time frame as stated in the document header. A description of the format can be found under: http://op.gfz-potsdam.de/champ/docs_CHAMP/CH-GFZ-FD-002.pdf', 'config_table': 'outputfileOrbit filename earthRotation earthRotationType inputfile filename orbits in CHORB format', 'display_text': 'This program reads in TerraSar-X or Tandem-X orbits in the special CHORB format and takes the appropriate time frame as stated in the document header. A description of the format can be found under: http://op.gfz-potsdam.de/champ/docs_CHAMP/CH-GFZ-FD-002.pdf'}, @@ -345,7 +355,7 @@ var documents = { 'gnssType': { 'name': 'gnssType', 'key': 'gnssType', 'description': 'A GnssType string consists of six parts (type, frequency, attribute, system, PRN, frequency number) represented by seven characters. The first three characters (representing type, frequency, and attribute) correspond to the observation codes of the . The satellite system character also follows the RINEX 3 definition: G = GPS R = GLONASS E = Galileo C = BeiDou S = SBAS J = QZSS I = IRNSS PRN is a two-digit number identifying a satellite. Frequency number is only used for GLONASS, where the range -7 to 14 is represented by letters starting with A. Each part of a GnssType string can be replaced by a wildcard \' * \', enabling the use of these strings as patterns, for example to select a subset of observations (e.g. C**G** matches all GPS code/range observations). Trailing wildcards are optional, meaning L1*R is automatically expanded to L1*R*** . For some RINEX 2 types (e.g. Galileo L5) the RINEX 3 attribute is unknown/undefined and can be replaced by ? , for example L5?E01 . Examples: C1CG23 = code/range observation, L1 frequency, derived from C/A code, GPS, PRN 23 L2PR05B = phase observation, G2 frequency, derived from P code, GLONASS, PRN 05, frequency number -6 *5*E** = all observation types, E5a frequency, all attributes, Galileo, all PRNs', 'config_table': '', 'display_text': 'A GnssType string consists of six parts (type, frequency, attribute, system, PRN, frequency number) represented by seven characters.

    • The first three characters (representing type, frequency, and attribute) correspond to the observation codes of the RINEX 3 definition.
    • The satellite system character also follows the RINEX 3 definition:
      • G = GPS
      • R = GLONASS
      • E = Galileo
      • C = BeiDou
      • S = SBAS
      • J = QZSS
      • I = IRNSS
    • PRN is a two-digit number identifying a satellite.
    • Frequency number is only used for GLONASS, where the range -7 to 14 is represented by letters starting with A.

    Each part of a GnssType string can be replaced by a wildcard \'*\', enabling the use of these strings as patterns, for example to select a subset of observations (e.g. C**G** matches all GPS code/range observations). Trailing wildcards are optional, meaning L1*R is automatically expanded to L1*R***. For some RINEX 2 types (e.g. Galileo L5) the RINEX 3 attribute is unknown/undefined and can be replaced by ?, for example L5?E01.

    Examples:

    • C1CG23 = code/range observation, L1 frequency, derived from C/A code, GPS, PRN 23
    • L2PR05B = phase observation, G2 frequency, derived from P code, GLONASS, PRN 05, frequency number -6
    • *5*E** = all observation types, E5a frequency, all attributes, Galileo, all PRNs
    '}, 'gravityfieldType': { 'name': 'gravityfieldType', 'key': 'gravityfieldType', 'description': 'This class computes functionals of the time depending gravity field, e.g potential, gravity anomalies or gravity gradients. If several instances of the class are given the results are summed up. Before summation every single result is multiplicated by a factor . To subtract a normal field like GRS80 from a potential to get the disturbance potential you must choose one factor by 1 and the other by -1. To get the mean of two fields just set each factor to 0.5. Some of the instances gives also information about the accuracy. The variance of the result (sum) is computed by means of variance propagation. Reads coefficients of a spherical harmonics expansion from file. The potential is given by If set the expansion is limited in the range between minDegree and maxDegree inclusivly. The computed result is multiplied with factor . If setSigmasToZero is true the variances are set to zero. This option is only important for variance propagation and does not change the result of the gravity field functionals. Reads coefficients of a spherical harmonics expansion (for inner space) from file. If set the expansion is limited in the range between minDegree and maxDegree inclusivly. The computed result is multiplied with factor . If setSigmasToZero is true the variances are set to zero. This option is only important for error propagation and does not change the result of the gravity field functionals. Reads a solution vector from file which may be computed by a least squares adjustment (e.g. by NormalsSolverVCE ). The coefficients of the vector are interpreted from position indexStart (counting from zero) with help of . If the solution file contains solution of several right hand sides you can choose one with number rightSide (counting from zero). You can also read a vector from file containing the accuracies of the coefficients. The computed result is multiplied with factor . Read a time variable gravity field from file represented by a spherical harmonics expansion in the spatial domain and spline functions in the time domain. If set the expansion is limited in the range between minDegree and maxDegree inclusivly. This file can be created for example by Gravityfield2TimeSplines or PotentialCoefficients2BlockMeanTimeSplines . The computed result is multiplied with factor . The given is interpreted as trend function and the result is computed at time as follows with is timeStart and is timeStep . The given is interpreted as oscillation function and the result is computed at time as follows with . A is only evaluated in the interval between timeStart inclusively and timeEnd exclusively. Outside the interval the result is zero. This class is useful to get a time series of monthly mean GRACE gravity field solutions. In each month another file of potentialCoefficients is valid. This can easily be created with . Treat as gravitational forces. The tides need a realization of to transform between the CRF and TRF and to compute rotational deformation from polar motion. It also needs from Sun, moon, and planets. The gravity is integrated from a topographic mass distribution. For each grid point in a prisma with density is assumed. The horizontal extension is computed from the grid spacing and the vertical extension is given by radialLowerBound and radialUpperBound above ellipsoid. All values are expressions and computed for each point with given data in the grid file. The standard variables for grids are available, see dataVariables . Example: The grid file contains the orthometric height of the topography in the first column, the geoid height in the second and the mean density of each prism in the third column. In this case the following settings should be used: radialUpperBound = data0+data1 , radialLowerBound = data1 , density = data2 . As the prim computation is time consuming a maximum distance around the evaluation point can defined with distancePrism . Afterwards a simplified radial line (the prism mass is concentrated to a line in the center) is used up to a distance of distanceLine . At last the prim is approximated by a point mass in the center up to a distance distanceMax (if set). Prisms nearby the evaluation point can be excluded with distanceMin . The given is interpreted as an oscillation function in the gravitational potential field, caused by large earthquakes. The result is computed at time as follows: with . In this equation, is the attenuation factor, is the overtone factor, is degree, is order, and is time in second. and are computed with the elastic Earth model or observed from the long period record of superconducting gravimeter measurements after the earthquakes. Convert to spherical harmonics and the coefficients. Groups a set of and has no further effect itself.', 'config_table': 'inputfilePotentialCoefficients filename minDegree uint maxDegree uint factor double the result is multiplied by this factor, set -1 to subtract the field setSigmasToZero boolean set variances to zero, should be used by adding back reference fields inputfilePotentialCoefficients filename minDegree uint maxDegree uint factor double the result is multiplied by this factor, set -1 to subtract the field setSigmasToZero boolean set variances to zero, should be used by adding back reference fields parametrization parametrizationGravityType inputfileSolution filename solution vector inputfileSigmax filename standards deviations or covariance matrix of the solution indexStart uint position in the solution vector rightSide uint if solution contains several right hand sides, select one factor double the result is multiplied by this factor, set -1 to subtract the field inputfileTimeSplinesGravityfield filename inputfileTimeSplinesCovariance filename minDegree uint maxDegree uint factor double the result is multiplied by this factor, set -1 to subtract the field gravityfield gravityfieldType this field is multiplicated by (time-time0)/timeStep timeStart time reference time timeStep time gravityfieldCos gravityfieldType multiplicated by cos(2pi/T(time-time0)) gravityfieldSin gravityfieldType multiplicated by sin(2pi/T(time-time0)) time0 time reference time period time [day] gravityfield gravityfieldType timeStart time first point in time timeEnd time last point in time will be less or equal timeEnd tides tidesType earthRotation earthRotationType ephemerides ephemeridesType inputfileGridRectangular filename Digital Terrain Model density expression expression [kg/m**3] radialUpperBound expression expression (variables \'height\', \'data\', \'L\', \'B\' and, \'area\' are taken from the gridded data radialLowerBound expression expression (variables \'height\', \'data\', \'L\', \'B\' and, \'area\' are taken from the gridded data distanceMin double [km] min. influence distance (ignore near zone) distancePrism double [km] max. distance for prism formular distanceLine double [km] max. distance for radial integration distanceMax double [km] max. influence distance (ignore far zone) factor double the result is multiplied by this factor, set -1 to subtract the field inputCoefficientMatrix filename oscillation model parameters time0 time the time earthquake happened minDegree uint maxDegree uint GM double Geocentric gravitational constant R double reference radius gravityfield gravityfieldType filter sphericalHarmonicsFilterType gravityfield gravityfieldType factor double the result is multiplied by this factor, set -1 to subtract the field', 'display_text': 'This class computes functionals of the time depending gravity field, e.g potential, gravity anomalies or gravity gradients.

    If several instances of the class are given the results are summed up. Before summation every single result is multiplicated by a factor. To subtract a normal field like GRS80 from a potential to get the disturbance potential you must choose one factor by 1 and the other by -1. To get the mean of two fields just set each factor to 0.5.

    Some of the instances gives also information about the accuracy. The variance of the result (sum) is computed by means of variance propagation.

    PotentialCoefficients

    Reads coefficients of a spherical harmonics expansion from file. The potential is given by \\[ V(\\lambda,\\vartheta,r) = \\frac{GM}{R}\\sum_{n=0}^\\infty \\sum_{m=0}^n \\left(\\frac{R}{r}\\right)^{n+1} \\left(c_{nm} C_{nm}(\\lambda,\\vartheta) + s_{nm} S_{nm}(\\lambda,\\vartheta)\\right). \\]If set the expansion is limited in the range between minDegree and maxDegree inclusivly. The computed result is multiplied with factor. If setSigmasToZero is true the variances are set to zero. This option is only important for variance propagation and does not change the result of the gravity field functionals.

    PotentialCoefficientsInterior

    Reads coefficients of a spherical harmonics expansion (for inner space) from file. If set the expansion is limited in the range between minDegree and maxDegree inclusivly. The computed result is multiplied with factor. If setSigmasToZero is true the variances are set to zero. This option is only important for error propagation and does not change the result of the gravity field functionals.

    FromParametrization

    Reads a solution vector from file inputfileSolution which may be computed by a least squares adjustment (e.g. by NormalsSolverVCE). The coefficients of the vector are interpreted from position indexStart (counting from zero) with help of parametrizationGravity. If the solution file contains solution of several right hand sides you can choose one with number rightSide (counting from zero). You can also read a vector from file inputfileSigmax containing the accuracies of the coefficients.

    The computed result is multiplied with factor.

    TimeSplines

    Read a time variable gravity field from file inputfileTimeSplinesGravityfield represented by a spherical harmonics expansion in the spatial domain and spline functions in the time domain. If set the expansion is limited in the range between minDegree and maxDegree inclusivly.

    This file can be created for example by Gravityfield2TimeSplines or PotentialCoefficients2BlockMeanTimeSplines.

    The computed result is multiplied with factor.

    Trend

    The given gravityfield is interpreted as trend function and the result is computed at time $t$ as follows \\[ V(\\M x,t) = \\frac{t-t_0}{\\Delta t}V(\\M x), \\]with $t_0$ is timeStart and $\\Delta t$ is timeStep.

    Oscillation

    The given gravityfield is interpreted as oscillation function and the result is computed at time $t$ as follows \\[ V(\\M x,t) = \\cos(\\omega)V_{cos}(\\M x)+\\sin(\\omega)V_{sin}(\\M x), \\]with $\\omega=\\frac{2\\pi}{T}(t-t_0)$.

    InInterval

    A gravityfield is only evaluated in the interval between timeStart inclusively and timeEnd exclusively. Outside the interval the result is zero.

    This class is useful to get a time series of monthly mean GRACE gravity field solutions. In each month another file of potentialCoefficients is valid. This can easily be created with loop.

    Tides

    Treat tides as gravitational forces. The tides need a realization of earthRotation to transform between the CRF and TRF and to compute rotational deformation from polar motion. It also needs ephemerides from Sun, moon, and planets.

    Topography

    The gravity is integrated from a topographic mass distribution. For each grid point in inputfileGridRectangular a prisma with density is assumed. The horizontal extension is computed from the grid spacing and the vertical extension is given by radialLowerBound and radialUpperBound above ellipsoid. All values are expressions and computed for each point with given data in the grid file. The standard variables for grids are available, see dataVariables.

    Example: The grid file contains the orthometric height of the topography in the first column, the geoid height in the second and the mean density of each prism in the third column. In this case the following settings should be used:

    • radialUpperBound = data0+data1,
    • radialLowerBound = data1,
    • density = data2.

    As the prim computation is time consuming a maximum distance around the evaluation point can defined with distancePrism. Afterwards a simplified radial line (the prism mass is concentrated to a line in the center) is used up to a distance of distanceLine. At last the prim is approximated by a point mass in the center up to a distance distanceMax (if set). Prisms nearby the evaluation point can be excluded with distanceMin.

    EarthquakeOscillation

    The given gravityfield is interpreted as an oscillation function in the gravitational potential field, caused by large earthquakes. The result is computed at time $t$ as follows: \\[ C_{lm}(\\M t) = \\sum_{n=0}^NC_{nlm}(1-\\cos(\\omega)\\exp(\\frac{-\\omega}{2Q_{nlm}})), \\]with $\\omega=\\frac{2\\pi}{T_{nlm}}(t-t_0)$. In this equation, $Q_{nlm}$ is the attenuation factor, $n$ is the overtone factor, $m$ is degree, $l$ is order, and $t$ is time in second. $T_{nlm}$ and $Q_{nlm}$ are computed with the elastic Earth model or observed from the long period record of superconducting gravimeter measurements after the earthquakes.

    Filter

    Convert gravityfield to spherical harmonics and filter the coefficients.

    Group

    Groups a set of gravityfield and has no further effect itself.'}, 'gridType': { 'name': 'gridType', 'key': 'gridType', 'description': 'This class generates a set of grid points. In a first step, the grid is always generated globally, with a regional subset of points can be extracted from the global grid. The parameters R and inverseFlattening define the shape of the ellipsoid on which the grid is generated. In case inverseFlattening is chosen as zero, a sphere is used. With height the distance of the points above the ellipsoid can be defined. In addition to the location of the points, weights are assigned to each of the points. These weights can be regarded as the surface element associated with each grid point. The geographical grid is an equal-angular point distribution with points located along meridians and along circles of latitude. deltaLambda denotes the angular difference between adjacent points along meridians and deltaPhi describes the angular difference between adjacent points along circles of latitude. The point setting results as follows: The number of grid points can be determined by The weights are calculated according to The zeroth level of densification coincides with the 12 icosahedron vertices, as displayed in the upper left part of Fig. . Then, depending on the envisaged densification, each triangle edge is divided into parts, illustrated in the upper right part of Fig. . The new nodes on the edges are then connected by arcs of great circles parallel to the triangle edges. The intersections of each three corresponding parallel lines become nodes of the densified grid as well. As in case of a spherical triangle those three connecting lines do not exactly intersect in one point, the center of the resulting triangle is used as location for the new node (lower left part of Fig. ). The lower right side of Fig. finally shows the densified triangle vertex grid for a level of . The number of grid points in dependence of the chosen level of densification can be calculated by The points of the zeroth level are located at the centers of the icosahedron triangles. To achieve a finer grid, each of the triangles is divided into four smaller triangles by connecting the midpoints of the triangle edges. The refined grid points are again located at the center of the triangles. Subsequently, the triangles can be further densified up to the desired level of densification , which is defined by level . The number of global grid points for a certain level can be determined by Thus the quantity of grid points depends exponentially on the level , as with every additional level the number of grid points quadruplicates. The grid features equiangular spacing along circles of latitude with parallelsCount defining the number of the parallels. Along the meridians the points are located at parallels at the zeros of the Legendre polynomial of degree , Consequently, the number of grid points sums up to The weights can be calculated according to The Reuter grid features equi-distant spacing along the meridians determined by the control parameter according to Thus denotes the number of points per meridian, as the two poles are included in the point distribution as well. Along the circles of latitude, the number of grid points decreases with increasing latitude in order to achieve an evenly distributed point pattern. This number is chosen, so that the points along each circle of latitude have the same spherical distance as two adjacent latitudes. The resulting relationship is given by The left hand side of this equation is the spherical distance between adjacent latitudes, the right hand side stands for the spherical distance between two points with the same polar distance and a longitudinal difference of . This longitudinal distance can be adjusted depending on to fulfill Eq. . The resulting formula for is The number of points for each circle of latitude can then be determined by Here the Gauss bracket specifies the largest integer equal to or less than . The longitudes are subsequently determined by The number of grid points can be estimated by The results from the fact that the are restricted to integer values. This kind of grid distributes an arbitrarily chosen number of points (defined by globalPointsCount ) following a recursive, quasi random sequence. In longitudinal direction the pattern follows This implies that every grid point features a unique longitude, with equi-angular longitudinal differences. The polar distance in the form for each point is determined by the following recursive sequence: Starting from an interval . If , then the midpoint of the interval is returned as result of the sequence, and the sequence is terminated. If the number of points is uneven, the midpoint is included into the list of . Subsequently, the interval is bisected into an upper and lower half, and the sequence is called for both halves. from upper and lower half are alternately sorted into the list of . The polar distances are calculated by The Driscoll-Healy grid, has equiangular spacing along the meridians as well as along the circles of latitude. In longitudinal direction (along the parallels), these angular differences for a given dimension coincide with those described for the corresponding geographical grid and Gauss grid. Along the meridians, the size of the latitudinal differences is half the size compared to the geographical grid. This results in the following point pattern, Consequently, the number of grid points is The weights are given by Creates one single point. Creates one single point. In this class grid is read from a file, which is given by . A corresponding file can be generated with GriddedDataCreate or with Matrix2GriddedData .', 'config_table': 'deltaLambda angle deltaPhi angle height double ellipsoidal height expression (variables \'height\', \'L\', \'B\') R double major axsis of the ellipsoid/sphere inverseFlattening double flattening of the ellipsoid, 0: sphere border borderType level uint division of icosahedron, point count = 10*(n+1)**2+2 R double major axsis of the ellipsoid/sphere inverseFlattening double flattening of the ellipsoid, 0: sphere border borderType level uint division of icosahedron, point count = 5*4**(n+1) R double major axsis of the ellipsoid/sphere inverseFlattening double flattening of the ellipsoid, 0: sphere border borderType parallelsCount uint R double major axsis of the ellipsoid/sphere inverseFlattening double flattening of the ellipsoid, 0: sphere border borderType gamma uint number of parallels height double ellipsoidal height R double major axsis of the ellipsoid/sphere inverseFlattening double flattening of the ellipsoid, 0: sphere border borderType globalPointsCount uint height double ellipsoidal height R double major axsis of the ellipsoid/sphere inverseFlattening double flattening of the ellipsoid, 0: sphere border borderType dimension uint number of parallels = 2*dimension height double ellipsoidal height R double major axsis of the ellipsoid/sphere inverseFlattening double flattening of the ellipsoid, 0: sphere border borderType L angle longitude B angle latitude height double ellipsoidal height area double associated area element on unit sphere R double major axsis of the ellipsoid/sphere inverseFlattening double flattening of the ellipsoid, 0: sphere x double [m] y double [m] z double [m] area double associated area element on unit sphere inputfileGrid filename border borderType', 'display_text': 'This class generates a set of grid points. In a first step, the grid is always generated globally, with border a regional subset of points can be extracted from the global grid. The parameters R and inverseFlattening define the shape of the ellipsoid on which the grid is generated. In case inverseFlattening is chosen as zero, a sphere is used. With height the distance of the points above the ellipsoid can be defined. In addition to the location of the points, weights are assigned to each of the points. These weights can be regarded as the surface element associated with each grid point.

    Geograph

    The geographical grid is an equal-angular point distribution with points located along meridians and along circles of latitude. deltaLambda denotes the angular difference between adjacent points along meridians and deltaPhi describes the angular difference between adjacent points along circles of latitude. The point setting results as follows: \\[ \\lambda_i=\\frac{\\Delta\\lambda}{2}+i\\cdot\\Delta\\lambda\\qquad\\mbox{with}\\qquad 0\\leq i< \\frac{360^\\circ}{\\Delta\\lambda}, \\]\\[ \\varphi_j=-90^\\circ+\\frac{\\Delta\\varphi}{2}+j\\cdot\\Delta\\varphi\\qquad\\mbox{with}\\qquad 0\\leq j<\\frac{180^\\circ}{\\Delta\\varphi}. \\]The number of grid points can be determined by \\[ I=\\frac{360^\\circ}{\\Delta\\lambda}\\cdot\\frac{180^\\circ}{\\Delta\\varphi}. \\]The weights are calculated according to \\[ w_i=\\int\\limits_{\\lambda_i-\\frac{\\Delta\\lambda}{2}}^{\\lambda_i+\\frac{\\Delta\\lambda}{2}}\\int\\limits_{\\vartheta_i-\\frac{\\Delta\\vartheta}{2}}^{\\vartheta_i+\\frac{\\Delta\\vartheta}{2}}=2\\cdot\\Delta\\lambda\\sin(\\Delta\\vartheta)\\sin(\\vartheta_i). \\]

    TriangleVertex

    The zeroth level of densification coincides with the 12 icosahedron vertices, as displayed in the upper left part of Fig. fig:triangle_grid. Then, depending on the envisaged densification, each triangle edge is divided into $n$ parts, illustrated in the upper right part of Fig. fig:triangle_grid. The new nodes on the edges are then connected by arcs of great circles parallel to the triangle edges. The intersections of each three corresponding parallel lines become nodes of the densified grid as well. As in case of a spherical triangle those three connecting lines do not exactly intersect in one point, the center of the resulting triangle is used as location for the new node (lower left part of Fig. fig:triangle_grid). The lower right side of Fig. fig:triangle_grid finally shows the densified triangle vertex grid for a level of $n=3$. The number of grid points in dependence of the chosen level of densification can be calculated by \\[\\label{eq:numberVertex} I=10\\cdot(n+1)^2+2. \\]

    TriangleCenter

    The points of the zeroth level are located at the centers of the icosahedron triangles. To achieve a finer grid, each of the triangles is divided into four smaller triangles by connecting the midpoints of the triangle edges. The refined grid points are again located at the center of the triangles. Subsequently, the triangles can be further densified up to the desired level of densification $n$, which is defined by level.

    The number of global grid points for a certain level can be determined by \\[\\label{eq:numberCenter} I=20\\cdot 4^n. \\]Thus the quantity of grid points depends exponentially on the level $n$, as with every additional level the number of grid points quadruplicates.

    Gauss

    The grid features equiangular spacing along circles of latitude with parallelsCount defining the number $L$ of the parallels. \\[ \\Delta\\lambda=\\frac{\\pi}{L}\\qquad\\Rightarrow\\qquad\\lambda_i=\\frac{\\Delta\\lambda}{2}+i\\cdot\\Delta\\lambda\\qquad\\mbox{with}\\qquad 0\\leq i< 2L. \\]Along the meridians the points are located at $L$ parallels at the $L$ zeros $\\vartheta_j$ of the Legendre polynomial of degree $L$, \\[ P_L(\\cos\\vartheta_j)=0. \\]Consequently, the number of grid points sums up to \\[ I=2\\cdot L^2. \\]The weights can be calculated according to \\[ w_i(L)=\\Delta\\lambda\\frac{2}{(1-t_i^2)(P\'_{L}(\\cos(\\vartheta _i)))^2},\\label{weights} \\]

    Reuter

    The Reuter grid features equi-distant spacing along the meridians determined by the control parameter $\\gamma$ according to \\[ \\Delta\\vartheta=\\frac{\\pi}{\\gamma}\\qquad\\Rightarrow\\vartheta_j=j\\Delta\\vartheta,\\qquad\\mbox{with}\\qquad 1\\leq j\\leq \\gamma-1. \\]Thus $\\gamma+1$ denotes the number of points per meridian, as the two poles are included in the point distribution as well. Along the circles of latitude, the number of grid points decreases with increasing latitude in order to achieve an evenly distributed point pattern. This number is chosen, so that the points along each circle of latitude have the same spherical distance as two adjacent latitudes. The resulting relationship is given by \\[\\label{eq:sphericalDistance} \\Delta\\vartheta=\\arccos\\left( \\cos^2\\vartheta_j+\\sin^2\\vartheta_j\\cos\\Delta\\lambda_j\\right). \\]The left hand side of this equation is the spherical distance between adjacent latitudes, the right hand side stands for the spherical distance between two points with the same polar distance $\\vartheta_j$ and a longitudinal difference of $\\Delta\\lambda_i$. This longitudinal distance can be adjusted depending on $\\vartheta_j$ to fulfill Eq. \\eqref{eq:sphericalDistance}. The resulting formula for $\\Delta\\lambda_i$ is \\[\\label{eq:deltaLambdai} \\Delta\\lambda_j=\\arccos\\left( \\frac{\\sin\\Delta\\vartheta -\\cos^2\\vartheta_j}{\\sin^2\\vartheta_j}\\right). \\]The number of points $\\gamma_j$ for each circle of latitude can then be determined by \\[\\label{eq:gammai} \\gamma_j=\\left[ \\frac{2\\pi}{\\Delta\\lambda_j}\\right] . \\]Here the Gauss bracket $[x]$ specifies the largest integer equal to or less than $x$. The longitudes are subsequently determined by \\[ \\lambda_{ij}=\\frac{\\Delta\\lambda_j}{2}+i\\cdot(2\\pi/\\gamma_j),\\qquad\\mbox{with}\\qquad 0\\leq i< \\gamma_j. \\]The number of grid points can be estimated by \\[\\label{eq:numberReuter} I=\\leq 2+\\frac{4}{\\pi}\\gamma^2, \\]The $\\leq$ results from the fact that the $\\gamma_j$ are restricted to integer values.

    Corput

    This kind of grid distributes an arbitrarily chosen number of $I$ points (defined by globalPointsCount) following a recursive, quasi random sequence. In longitudinal direction the pattern follows \\[ \\Delta\\lambda=\\frac{2\\pi}{I}\\qquad\\Rightarrow\\qquad\\frac{\\Delta\\lambda}{2}+\\lambda_i=i\\cdot\\Delta\\lambda\\qquad\\mbox{with}\\qquad 1\\leq i\\leq I. \\]This implies that every grid point features a unique longitude, with equi-angular longitudinal differences.

    The polar distance in the form $t_i=\\cos\\vartheta_i$ for each point is determined by the following recursive sequence:

    • Starting from an interval $t\\in[-1,1]$.
    • If $I=1$, then the midpoint of the interval is returned as result of the sequence, and the sequence is terminated.
    • If the number of points is uneven, the midpoint is included into the list of $t_i$.
    • Subsequently, the interval is bisected into an upper and lower half, and the sequence is called for both halves.
    • $t$ from upper and lower half are alternately sorted into the list of $t_i$.
    • The polar distances are calculated by \\[ \\vartheta_i=\\arccos\\, t_i. \\]

    Driscoll

    The Driscoll-Healy grid, has equiangular spacing along the meridians as well as along the circles of latitude. In longitudinal direction (along the parallels), these angular differences for a given dimension $L$ coincide with those described for the corresponding geographical grid and Gauss grid. Along the meridians, the size of the latitudinal differences is half the size compared to the geographical grid. This results in the following point pattern, \\[ \\begin{split} \\Delta\\lambda=\\frac{\\pi}{L}\\qquad&\\Rightarrow\\qquad\\lambda_i=\\frac{\\Delta\\lambda}{2}+i\\cdot\\Delta\\lambda\\qquad&\\mbox{with}\\qquad 0\\leq i< 2L, \\\\ \\Delta\\vartheta=\\frac{\\pi}{2L}\\qquad&\\Rightarrow\\qquad\\vartheta_j=j\\cdot\\Delta\\vartheta\\qquad&\\mbox{with}\\qquad 1\\leq j\\leq 2L. \\end{split} \\]Consequently, the number of grid points is \\[ I=4\\cdot L^2. \\]The weights are given by \\[ w_i=\\Delta\\lambda\\frac{4}{2L}\\sin(\\vartheta_i)\\sum_{l=0}^{L-1}\\frac{\\sin\\left[ (2l+1)\\;\\vartheta_i\\right] }{2l+1}. \\]

    SinglePoint

    Creates one single point.

    SinglePointCartesian

    Creates one single point.

    File

    In this class grid is read from a file, which is given by inputfileGrid. A corresponding file can be generated with GriddedDataCreate or with Matrix2GriddedData.'}, -'instrumentTypeType': { 'name': 'instrumentTypeType', 'key': 'instrumentTypeType', 'description': 'Defines the type of an instrument file .', 'config_table': 'instrumentTypeType choice instrument type INSTRUMENTTIME time without data MISCVALUE single value MISCVALUES multiple values VECTOR3D x, y, z COVARIANCE3D xx, yy, zz, xy, xz, yz ORBIT position [m], velocity [m/s], acceleration [m/s^2] (each x, y, z) STARCAMERA quaternions (q0, qx, qy, qz) ACCELEROMETER x, y, z [m/s^2] SATELLITETRACKING range [m], range rate [m/s], range acceleration [m/s^2] GRADIOMETER xx, yy, zz, xy, xz, yz [1/s^2] GNSSRECEIVER GNSS phase/code observations [m] OBSERVATIONSIGMA accuracy MASS THRUSTER MAGNETOMETER ACCHOUSEKEEPING', 'display_text': 'Defines the type of an instrument file.'}, +'instrumentTypeType': { 'name': 'instrumentTypeType', 'key': 'instrumentTypeType', 'description': 'Defines the type of an instrument file .', 'config_table': 'instrumentTypeType choice instrument type INSTRUMENTTIME time without data MISCVALUE single value MISCVALUES multiple values VECTOR3D x, y, z COVARIANCE3D xx, yy, zz, xy, xz, yz ORBIT position [m], velocity [m/s], acceleration [m/s^2] (each x, y, z) STARCAMERA quaternions (q0, qx, qy, qz) ACCELEROMETER x, y, z [m/s^2] SATELLITETRACKING range [m], range rate [m/s], range acceleration [m/s^2] GRADIOMETER xx, yy, zz, xy, xz, yz [1/s^2] GNSSRECEIVER GNSS phase/code observations [m] OBSERVATIONSIGMA accuracy SATELLITELASERRANGING range [m], accuracy [m], redundancy, window [s], wavelength [m], azimuth [rad], elevation [rad] METEOROLOGICAL temperature [K], pressure [Pa], humidity [%], windSpeed [m/s], radiation [W/m^2], precip. [mm/d] MASS THRUSTER MAGNETOMETER ACCHOUSEKEEPING', 'display_text': 'Defines the type of an instrument file.'}, 'interpolatorTimeSeriesType': { 'name': 'interpolatorTimeSeriesType', 'key': 'interpolatorTimeSeriesType', 'description': 'This class resamples data of a times series to new poins in time. Polynomial prediction using a moving polynomial of polynomialDegree . The optimal polynomial is chosen based on the centricity of the data points around the resampling point and the distance to all polynomial data points. All polynomial data points must be within maxDataPointRange . Resampling points within maxExtrapolationDistance of the polynomial will be extrapolated. The elements maxDataPointRange and maxExtrapolationDistance are given in the unit of seconds. If negative values are used, the unit is relative to the median input sampling. A polynomial of polynomialDegree is estimated using all data points within maxDataPointDistance of the resampling point. This polynomial is then used to predict the resampling point. A resampling point will be extrapolated if there are only data points before/after as long as the closest one is within maxExtrapolationDistance . The elements maxDataPointDistance and maxExtrapolationDistance are given in the unit of seconds. If negative values are used, the unit is relative to the median input sampling.', 'config_table': 'polynomialDegree uint degree of the moving polynomial maxDataPointRange double [seconds] all degree+1 data points must be within this range for a valid polynomial maxExtrapolationDistance double [seconds] resampling points within this range of the polynomial will be extrapolated polynomialDegree uint degree of the estimated polynomial maxDataPointDistance double [seconds] all data points within this distance around the resampling point will be used maxExtrapolationDistance double [seconds] resampling points within this range of the polynomial will be extrapolated polynomialDegree uint degree of the estimated polynomial maxDataGap double [seconds] max data gap to interpolate maxDataSpan double [seconds] time span on each side used for least squares fit margin double [seconds] margin for identical times', 'display_text': 'This class resamples data of a times series to new poins in time.

    Polynomial

    Polynomial prediction using a moving polynomial of polynomialDegree. The optimal polynomial is chosen based on the centricity of the data points around the resampling point and the distance to all polynomial data points. All polynomial data points must be within maxDataPointRange. Resampling points within maxExtrapolationDistance of the polynomial will be extrapolated. The elements maxDataPointRange and maxExtrapolationDistance are given in the unit of seconds. If negative values are used, the unit is relative to the median input sampling.

    Least squares polynomial fit

    A polynomial of polynomialDegree is estimated using all data points within maxDataPointDistance of the resampling point. This polynomial is then used to predict the resampling point. A resampling point will be extrapolated if there are only data points before/after as long as the closest one is within maxExtrapolationDistance. The elements maxDataPointDistance and maxExtrapolationDistance are given in the unit of seconds. If negative values are used, the unit is relative to the median input sampling.

    Fill gaps with least squares polynomial fit

    '}, 'kernelType': { 'name': 'kernelType', 'key': 'kernelType', 'description': 'Kernel defines harmonic isotropic integral kernels . where is the (disturbance)potential and is a functional on the spherical surface . The Kernel can be exapanded into a series of (fully normalized) legendre polynomials On the one hand the kernel defines the type of the functionals that are measured or have to be computed, e.g. gravity anomalies given by the Stokes-kernel. On the other hand the kernel functions can be used as basis functions to represent the gravity field, e.g. as spline functions or wavelets. The geoid height is defined by Bruns formula with the disturbance potential and the normal gravity and where is the ellipsoidal height in meter and the longitude. The kernel is given by and the coefficients in are Gravity anomalies in linearized form are defined by The Stokes kernel is given by and the coefficients in are Gravity disturbances in linearized form are defined by The Hotine kernel is given by and the coefficients in are The Abel-Poisson kernel is given by and the coefficients in are This kernel defines a point mass or mass on a single layer ( -kernel) taking the effect of the loading into account. The coefficients of the kernel defined in are where is the gravitational constant and are the load Love numbers. Height of equivalent water columns taking the effect of the loading into account. The coefficients of the kernel defined in are where is the gravitational constant, is the density of water and are the load Love numbers. Ocean bottom pressure caused by water and atmosphere masses columns taking the effect of the loading into account. The coefficients of the kernel defined in are where is the gravitational constant, is the normal gravity and are the load Love numbers. Computes the radial deformation caused by loading. The coefficients of the kernel defined in are where is the normal gravity defined in , and are the load Love numbers and the load deformation Love numbers. This kernel defines the second radial derivative of the (disturbance) potential. The coefficients of the kernel defined in are The kernel is defined by the coefficients given by file. Another is smoothed by a gauss filter which is defined by with where is the given smoothing radius in km and km is the Earth radius. The coefficients of the kernel are multiplicated by Another is smoothed by a Blackman low-pass filter. The filter is defined through the beginning and end of the transition from pass-band to stop-band. This transition band is specified by startDegreeTransition ( ) and stopDegreeTransition ( ). The coefficients of this kernel are defined as with Another is truncated before minDegree and after maxDegree . The coefficients of this kernel are defined as The selenoid height is defined by Bruns formula with the disturbance potential and the normal gravity of the moon. The kernel is given by and the coefficients in are', 'config_table': 'inputfileLoadingLoveNumber filename density double [kg/m**3] inputfileLoadingLoveNumber filename inputfileLoadingLoveNumber filename inputfileDeformationLoadLoveNumber filename inputfilePotentialLoadLoveNumber filename if full potential is given and not only loading potential inputfileCoefficients filename kernel kernelType radius double filter radius [km] kernel kernelType startDegreeTransition uint minimum degree in transition band stopDegreeTransition uint maximum degree in transition band kernel kernelType minDegree uint truncate before minDegree maxDegree uint truncate after maxDegree', 'display_text': 'Kernel defines harmonic isotropic integral kernels $K$. \\[ T(P) = \\frac{1}{4\\pi}\\int_\\Omega K(P,Q)\\cdot f(Q)\\,d\\Omega(Q), \\]where $T$ is the (disturbance)potential and $f$ is a functional on the spherical surface $\\Omega$. The Kernel can be exapanded into a series of (fully normalized) legendre polynomials \\[\\label{eq.kernel} K(\\cos\\psi,r,R) = \\sum_n \\left(\\frac{R}{r}\\right)^{n+1} k_n\\sqrt{2n+1}\\bar{P}_n(\\cos\\psi). \\]On the one hand the kernel defines the type of the functionals $f$ that are measured or have to be computed, e.g. gravity anomalies given by the Stokes-kernel. On the other hand the kernel functions can be used as basis functions to represent the gravity field, e.g. as spline functions or wavelets.

    GeoidHeight

    The geoid height is defined by Bruns formula \\[ N = \\frac{1}{\\gamma}T \\]with $T$ the disturbance potential and the normal gravity \\[\\label{normalgravity} \\gamma = \\gamma_0 - 0.30877\\cdot 10^{-5}/s^2(1-0.00142\\sin^2(B))h \\]and \\[ \\gamma_0 = 9.780327\\,m/s^2(1+0.0053024\\sin^2(B)-0.0000058\\sin^2(2B)) \\]where $h$ is the ellipsoidal height in meter and $B$ the longitude.

    The kernel is given by \\[ K(\\cos\\psi,r,R) = \\gamma\\frac{R(r^2-R^2)}{l^3}, \\]and the coefficients in \\eqref{eq.kernel} are \\[ k_n = \\gamma. \\]

    Anomalies

    Gravity anomalies in linearized form are defined by \\[ \\Delta g = -\\frac{\\partial T}{\\partial r}-\\frac{2}{r}T. \\]The Stokes kernel is given by \\[ K(\\cos\\psi,r,R) = \\frac{2R^2}{l}-3\\frac{Rl}{r^2}-\\frac{R^2}{r^2}\\cos\\psi \\left(5+3\\ln\\frac{l+r-R\\cos\\psi}{2r}\\right), \\]and the coefficients in \\eqref{eq.kernel} are \\[ k_n = \\frac{R}{n-1}. \\]

    Disturbance

    Gravity disturbances in linearized form are defined by \\[ \\delta g = -\\frac{dT}{dr}. \\]The Hotine kernel is given by \\[ K(\\cos\\psi,r,R) = \\frac{2R^2}{l}-R\\ln\\frac{l+R-r\\cos\\psi}{r(1-\\cos\\psi)}, \\]and the coefficients in \\eqref{eq.kernel} are \\[ k_n = \\frac{R}{n+1}. \\]

    Potential

    The Abel-Poisson kernel is given by \\[ K(\\cos\\psi,r,R) = \\frac{R(r^2-R^2)}{l^3}, \\]and the coefficients in \\eqref{eq.kernel} are \\[ k_n = 1. \\]

    Density

    This kernel defines a point mass or mass on a single layer ($1/l$-kernel) taking the effect of the loading into account.

    The coefficients of the kernel defined in \\eqref{eq.kernel} are \\[ k_n = 4\\pi G R\\frac{1+k_n\'}{2n+1}, \\]where $G$ is the gravitational constant and $k_n\'$ are the load Love numbers.

    WaterHeight

    Height of equivalent water columns taking the effect of the loading into account.

    The coefficients of the kernel defined in \\eqref{eq.kernel} are \\[ k_n = 4\\pi G \\rho R\\frac{1+k_n\'}{2n+1}, \\]where $G$ is the gravitational constant, $\\rho$ is the density of water and $k_n\'$ are the load Love numbers.

    BottomPressure

    Ocean bottom pressure caused by water and atmosphere masses columns taking the effect of the loading into account.

    The coefficients of the kernel defined in \\eqref{eq.kernel} are \\[ k_n = \\frac{4\\pi G R }{\\gamma}\\frac{1+k_n\'}{2n+1}, \\]where $G$ is the gravitational constant, $\\gamma$ is the normal gravity and $k_n\'$ are the load Love numbers.

    Deformation

    Computes the radial deformation caused by loading.

    The coefficients of the kernel defined in \\eqref{eq.kernel} are \\[ k_n = \\gamma\\frac{1+k_n\'}{h_n\'}, \\]where $\\gamma$ is the normal gravity defined in \\eqref{normalgravity}, $h_n\'$ and $k_n\'$ are the load Love numbers and the load deformation Love numbers.

    RadialGradient

    This kernel defines the second radial derivative of the (disturbance) potential. \\[ T_{rr} = \\frac{\\partial^2 T}{\\partial r^2}. \\]The coefficients of the kernel defined in \\eqref{eq.kernel} are \\[ k_n = \\frac{r^2}{(n+1)(n+2)}. \\]

    Coefficients

    The kernel is defined by the coefficients $k_n$ given by file.

    FilterGauss

    Another kernel is smoothed by a gauss filter which is defined by \\[ F(\\cos\\psi) = \\frac{b\\cdot e^{-b(1-\\cos\\psi)}}{1-e^{-2b}} \\]with $b = \\frac{ln(2)}{1-\\cos(r/R)}$ where $r$ is the given smoothing radius in km and $R=6378.1366$ km is the Earth radius. The coefficients $k_n$ of the kernel are multiplicated by \\[ f_n = \\frac{1}{2n+1} \\int_{-1}^1 F(t)\\cdot \\bar{P}_n(t)\\,dt. \\]

    BlackmanLowpass

    Another kernel is smoothed by a Blackman low-pass filter. The filter is defined through the beginning and end of the transition from pass-band to stop-band. This transition band is specified by startDegreeTransition ($n_1$) and stopDegreeTransition ($n_2$).

    The coefficients of this kernel are defined as \\[ \\begin{cases} 1 & \\text{for } n < n_1 \\\\ A_n^2 & \\text{for } n_1\\leq n \\leq n_2 \\\\ 0 & \\text{for } n > n_2 \\\\ \\end{cases} \\]with \\[ A_n = 0.42 + 0.5\\cos(\\pi \\frac{n-n_1}{n_2-n_1}) + 0.08 \\cos(2\\pi\\frac{n-n_1}{n_2-n_1}). \\]

    Truncation

    Another kernel is truncated before minDegree and after maxDegree. The coefficients of this kernel are defined as \\[ k_n = \\begin{cases} 1 & \\text{for } n_{\\text{minDegree}} \\leq n \\leq n_{\\text{maxDegree}}\\\\ 0 & \\text{else.} \\\\ \\end{cases} \\]

    SelenoidHeight

    The selenoid height is defined by Bruns formula \\[ N = \\frac{1}{\\gamma}T \\]with $T$ the disturbance potential and the normal gravity $\\gamma=\\frac{GM}{R^2}$ of the moon.

    The kernel is given by \\[ K(\\cos\\psi,r,R) = \\gamma\\frac{R(r^2-R^2)}{l^3}, \\]and the coefficients in \\eqref{eq.kernel} are \\[ k_n = \\gamma. \\]'}, 'loopType': { 'name': 'loopType', 'key': 'loopType', 'description': 'Generates a sequence with variables to loop over. The variable names can be set with variableLoop... and the current values are assigned to the variables for each loop step. With only a subset of loop steps are performed. The variableLoopIndex and variableLoopCount are not affected by the condition. The result would therefore be the same as using LoopPrograms with a nested IfPrograms . See Loop and conditions for usage. Loop over points in time. Loop over the intervals between points in time. Loop over list of strings. Loop over rows of a table containing strings. The table can be defined rowWise or columnWise . Each row/column must have the same number of cells. Loop over list of strings from files. Loop over rows of a table containing strings. Each row must have the same number of columns. Loop over lines of a text file. Loop over rows of a matrix. To define the loop variables the standard data variables of the matrix are available, see dataVariables . Loop over sequence of numbers. Loop over files of a directory. Loop over lines of command output. Loop over nested loops. First loop is outermost loop, every subsequent loop is one level below the previous loop . Loop over specific equipment of a platform file . DEPRECATDED. Use LoopPlatformEquipment instead.', 'config_table': 'timeSeries timeSeriesType loop is called for every point in time variableLoopTime string variable with time of each loop variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step timeIntervals timeSeriesType loop is called for every interval variableLoopTimeStart string variable with starting time of each interval variableLoopTimeEnd string variable with ending time of each interval variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step string string explicit list of strings variableLoopString string name of the variable to be replaced variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step table choice define table by rows/columns rowWise sequence define table by rows row sequence define table by rows cell string explicit list of cells in row/column columnWise sequence define table by columns column sequence define table by columns cell string explicit list of cells in row/column variableLoopString string 1. variable name for the 1. column, next variable name for the 2. column, ... variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step inputfile filename simple ASCII file with strings (separated by whitespace) sort boolean sort entries alphabetically (ascending) removeDuplicates boolean remove duplicate entries (order is preserved) startIndex uint start at element startIndex (counting from 0) count uint use count elements (default: use all) variableLoopString string name of the variable to be replaced variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step inputfile filename simple ASCII file with multiple columns (separated by whitespace) startLine uint start at line startLine (counting from 0) countLines uint read count lines (default: all) variableLoopString string 1. variable name for the 1. column, next variable name for the 2. column, ... variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step inputfile filename simple ASCII file with lines sort boolean sort lines alphabetically (ascending) removeDuplicates boolean remove duplicate lines (order is preserved) startIndex uint start at element startIndex (counting from 0) count uint use number of lines only (default: use all) variableLoopLine string name of the variable to be replaced variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step inputfile filename transpose boolean effectively loop over columns startRow expression start at this row (variable: rows) countRows expression use this many rows (variable: rows) variableLoop expression define a variable by name = expression (input columns are named data0, data1, ...) variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step rangeStart double start of range rangeEnd double end of range (inclusive) sampling double sampling variableLoopNumber string name of the variable to be replaced variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step directory filename directory pattern string wildcard pattern isRegularExpression boolean pattern is a regular expression variableLoopFile string name of the variable to be replaced variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step command filename each output line becomes a loop iteration silently boolean without showing the output. variableLoopString string name of the variable to be replaced variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step loop loopType subloop variableLoopIndex string variable with index of current iteration (starts with zero) condition conditionType check before each loop step inputfilePlatform filename platform info file equipmentType choice equipment type to loop over all loop over all types gnssAntenna loop over antennas gnssReceiver loop over receivers slrStation loop over SLR stations slrRetroReflector loop over laser retroreflectors satelliteIdentifier loop over satellite identifiers other loop over other types variableLoopName string variable with name variableLoopSerial string variable with serial variableLoopInfo string variable with radome (antenna) or version (receiver) variableLoopTimeStart string variable with start time variableLoopTimeEnd string variable with end time variableLoopPositionX string variable with position x variableLoopPositionY string variable with position y variableLoopPositionY string variable with position z variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step inputfileGnssStationInfo filename station/transmitter info file infoType choice info to loop over antenna loop over antennas receiver loop over receivers variableLoopName string variable with antenna/receiver name variableLoopSerial string variable with antenna/receiver serial variableLoopInfo string variable with radome (antenna) or version (receiver) variableLoopTimeStart string variable with antenna/receiver start time variableLoopTimeEnd string variable with antenna/receiver end time variableLoopIndex string variable with index of current iteration (starts with zero) variableLoopCount string variable with total number of iterations condition conditionType check before each loop step', 'display_text': 'Generates a sequence with variables to loop over. The variable names can be set with variableLoop... and the current values are assigned to the variables for each loop step.

    With condition only a subset of loop steps are performed. The variableLoopIndex and variableLoopCount are not affected by the condition. The result would therefore be the same as using LoopPrograms with a nested IfPrograms.

    See Loop and conditions for usage.

    TimeSeries

    Loop over points in time.

    TimeIntervals

    Loop over the intervals between points in time.

    ManualList

    Loop over list of strings.

    ManualTable

    Loop over rows of a table containing strings. The table can be defined rowWise or columnWise. Each row/column must have the same number of cells.

    FileAscii

    Loop over list of strings from files.

    FileAsciiTable

    Loop over rows of a table containing strings. Each row must have the same number of columns.

    FileLines

    Loop over lines of a text file.

    Matrix

    Loop over rows of a matrix. To define the loop variables the standard data variables of the matrix are available, see dataVariables.

    UniformSampling

    Loop over sequence of numbers.

    DirectoryListing

    Loop over files of a directory.

    CommandOutput

    Loop over lines of command output.

    Loop

    Loop over nested loops. First loop is outermost loop, every subsequent loop is one level below the previous loop.

    PlatformEquipment

    Loop over specific equipment of a platform file.

    FileGnssStationInfo

    DEPRECATDED. Use LoopPlatformEquipment instead.'}, @@ -364,7 +374,7 @@ var documents = { 'parametrizationSatelliteTrackingType': { 'name': 'parametrizationSatelliteTrackingType', 'key': 'parametrizationSatelliteTrackingType', 'description': 'This class defines parameters of Satellite-to-Satellite tracking observations. It will be used to set up the design matrix in a least squares adjustment. If multiple parametrizations are given the coefficients in the parameter vector are sequently appended. Estimate the KBR antenna phase centre (APC) coordinates in for each spacecraft in satellite reference frame (SRF) as constant per axis. The observation equations are computed by taking the derivative of the antenna offset correction equation w.r.t. the KBR APC coordinates. The parameter names are satellite1.satellite2:sstAntennaCenter1.x:*:* , satellite1.satellite2:sstAntennaCenter1.y:*:* , satellite1.satellite2:sstAntennaCenter1.z:*:* , satellite1.satellite2:sstAntennaCenter2.x:*:* , satellite1.satellite2:sstAntennaCenter2.y:*:* , satellite1.satellite2:sstAntennaCenter2.z:*:* . Estimate bias for SST observations in or ]. The temporal variation is defined by . The parameter names are satellite1.satellite2:sstBias:<temporal>:<interval> . Estimate scale factor for SST observations with respect to reference SST data . The temporal variation is defined by . The parameter names are satellite1.satellite2:sstScale:<temporal>:<interval> . Estimate time shift in seconds in SST observations, with defined temporal variation by . The design matrix is computed by taking the derivative of the ranging data w.r.t. time. The parameter names are satellite1.satellite2:sstTimeBias:<temporal>:<interval> . Estimate scale factors for deterministic signal models from satellite tracking instrument file , see EnsembleAveragingScaleModel . Amplitude variation of model waveforms is defined by . The parameter names are satellite1.satellite2:scaleModel:<temporal>:<interval> . Estimate deterministic signals in the GRACE K-Band measurements caused by Sun intrusions into the star camera baffles of GRACE-A and eclipse transits of the satellites. These events can be time-indexed beforehand using satellite position and orientation, see GraceSstSpecialEvents . The shape of this short-period waveform is nearly constant within one month and can be approximated by a polynomial. The amplitude variation of the waveform can also be taken into account by . The parameter names are satellite1.satellite2:<type>.legendrePolynomial.n<degree>:<temporal>:<interval> .', 'config_table': 'estimate1X boolean along (satellite 1) estimate1Y boolean cross (satellite 1) estimate1Z boolean nadir (satellite 1) estimate2X boolean along (satellite 2) estimate2Y boolean cross (satellite 2) estimate2Z boolean nadir (satellite 2) interpolationDegree uint differentiation by polynomial approximation of degree n temporal parametrizationTemporalType perArc boolean inputfileSatelliteTracking filename temporal parametrizationTemporalType perArc boolean polynomialDegree uint polynomial degree temporal parametrizationTemporalType perArc boolean inputfileSatelliteTracking filename temporal parametrizationTemporalType perArc boolean inputfileEvents filename instrument with GRACE events type choice eclipse1 eclipse2 starCameraBox1 starCameraBox2 starCameraBox3 starCameraBox4 starCameraBox5 starCameraBox6 marginLeft double margin size (on both sides) [seconds] marginRight double margin size (on both sides) [seconds] minNumberOfEvents uint min. number of events to setup parameters polynomialDegree uint polynomial degree temporal parametrizationTemporalType', 'display_text': 'This class defines parameters of Satellite-to-Satellite tracking observations. It will be used to set up the design matrix in a least squares adjustment. If multiple parametrizations are given the coefficients in the parameter vector are sequently appended.

    AntennaCenter

    Estimate the KBR antenna phase centre (APC) coordinates in $[m]$ for each spacecraft in satellite reference frame (SRF) as constant per axis. The observation equations are computed by taking the derivative of the antenna offset correction equation w.r.t. the KBR APC coordinates.

    The parameter names are

    • satellite1.satellite2:sstAntennaCenter1.x:*:*,
    • satellite1.satellite2:sstAntennaCenter1.y:*:*,
    • satellite1.satellite2:sstAntennaCenter1.z:*:*,
    • satellite1.satellite2:sstAntennaCenter2.x:*:*,
    • satellite1.satellite2:sstAntennaCenter2.y:*:*,
    • satellite1.satellite2:sstAntennaCenter2.z:*:*.

    Bias

    Estimate bias for SST observations in $[m]$ or $[m/s$]. The temporal variation is defined by parametrizationTemporal.

    The parameter names are satellite1.satellite2:sstBias:<temporal>:<interval>.

    Scale

    Estimate scale factor for SST observations with respect to reference SST data inputfileSatelliteTracking. The temporal variation is defined by parametrizationTemporal.

    The parameter names are satellite1.satellite2:sstScale:<temporal>:<interval>.

    TimeBias

    Estimate time shift in seconds in SST observations, with defined temporal variation by parametrizationTemporal. The design matrix is computed by taking the derivative of the ranging data w.r.t. time.

    The parameter names are satellite1.satellite2:sstTimeBias:<temporal>:<interval>.

    ScaleModel

    Estimate scale factors for deterministic signal models from satellite tracking instrument file inputfileSatelliteTracking, see EnsembleAveragingScaleModel. Amplitude variation of model waveforms is defined by parametrizationTemporal.

    The parameter names are satellite1.satellite2:scaleModel:<temporal>:<interval>.

    SpecialEffect

    Estimate deterministic signals in the GRACE K-Band measurements caused by Sun intrusions into the star camera baffles of GRACE-A and eclipse transits of the satellites. These events can be time-indexed beforehand using satellite position and orientation, see GraceSstSpecialEvents. The shape of this short-period waveform is nearly constant within one month and can be approximated by a polynomial. The amplitude variation of the waveform can also be taken into account by parametrizationTemporal.

    The parameter names are satellite1.satellite2:<type>.legendrePolynomial.n<degree>:<temporal>:<interval>.'}, 'parametrizationTemporalType': { 'name': 'parametrizationTemporalType', 'key': 'parametrizationTemporalType', 'description': 'This class gives a parametrization of time depending parameters (gravity field, positions, ...). It will be used to set up the design matrix in a least squares adjustment. If multiple parametrizations are given the coefficients in the parameter vector are sequently appended. Useally time intervals are defined half open meaning the last time belongs not to the interval. This behaviour can be changed for the last interval with includeLastTime . Represents a parameter being constant in time in each interval . The parameter names are *:*:*:<interval> . A time variable function is given by a linear trend with is timeStart and is timeStep in days. A constant term is not included and must added separately. The parameter name is *:*:trend.<timeStep(days)>*(t-<timeStart>):* . A time variable function is given by with the (spatial) coefficients as parameters and the temporal basis functions . Basis splines are defined as polynomials of degree in intervals between nodal points in time , for details see basis splines . The parameters are ordered timewise. First all parameters of then and so on. The total parameter count in each interval is , where is the count of time points from in each interval and is the degree . The parameter names are *:*:spline.n<degree>:<interval of each spline> . A time variable function is represented by Legendre polynomials in each interval . The time is normed to in each interval. The total parameter count is , where is the polynmial degree and the number of intervals with the parameter names *:*:legendrePolynomial.n<degree>:<interval> . A time variable function is given by a oscillation with , is timeStart and is timePeriod in days. The parameter names are *:*:oscillation.cos(2*pi/<period(days)>*(t-<timeStart>)):* and *:*:oscillation.sin(2*pi/<period(days)>*(t-<timeStart>)):* . A time variable function is given by a fourier expansion with the normalized time and is timeStart , is timeEnd in each interval and is the fourierDegree . The total parameter count is , where is the number of intervals. The parameters are sorted in following order: with the parameter names *:*:fourier.cos(<m>*x):<interval> and *:*:fourier.sin(<m>*x):<interval> . The time variable function is given by a fourier expansion where are the arguments of the tide constituents where are the Doodson\'s fundamental arguments ( ) and are the Doodson multipliers for the term at frequency . The multipliers must be given by coded as Doodson number (e.g. 255.555) or as names intoduced by Darwin (e.g. M2). The major constituents given by can be used to interpolate minor tidal constituents using the file . This file can be created with DoodsonHarmonicsCalculateAdmittance . The total parameter count is with the number of doodson frequencies. The parameters are sorted in following order: with the parameter names *:*:doodson.cos(<doodsonName>):* and *:*:doodson.sin(<doodsonName>):* .', 'config_table': 'interval timeSeriesType includeLastTime boolean timeStart time reference time timeStep time degree uint degree of splines timeSeries timeSeriesType nodal points in time domain intervals timeSeriesType includeLastTime boolean polynomialDegree uint polynomial degree interval timeSeriesType intervals of polynomials includeLastTime boolean period time [day] time0 time reference time fourierDegree uint interval timeSeriesType intervals of fourier series includeLastTime boolean doodson doodson code number (e.g. 255.555) or darwin name (e.g. M2) inputfileAdmittance filename interpolation of minor constituents', 'display_text': 'This class gives a parametrization of time depending parameters (gravity field, positions, ...). It will be used to set up the design matrix in a least squares adjustment. If multiple parametrizations are given the coefficients in the parameter vector are sequently appended.

    Useally time intervals are defined half open meaning the last time belongs not to the interval. This behaviour can be changed for the last interval with includeLastTime.

    Constant

    Represents a parameter being constant in time in each interval.

    The parameter names are *:*:*:<interval>.

    Trend

    A time variable function is given by a linear trend \\[ f(x,t) = \\frac{1}{T}(t-t_0) \\cdot f_t(x), \\]with $t_0$ is timeStart and $T$ is timeStep in days. A constant term is not included and must added separately.

    The parameter name is *:*:trend.<timeStep(days)>*(t-<timeStart>):*.

    Splines

    A time variable function is given by \\[ f(x,t) = \\sum_i f_i(x)\\Psi_i(t), \\]with the (spatial) coefficients $f_i(x)$ as parameters and the temporal basis functions $\\Psi_i(t)$. Basis splines are defined as polynomials of degree $n$ in intervals between nodal points in time $t_i$, for details see basis splines.

    The parameters are ordered timewise. First all parameters of $f_{i=1}(x)$ then $f_{i=2}(x)$ and so on. The total parameter count in each interval is $N=N_t+d-1$, where $N_t$ is the count of time points from timeSeries in each interval and $d$ is the degree.

    The parameter names are *:*:spline.n<degree>:<interval of each spline>.

    Polynomial

    A time variable function is represented by Legendre polynomials in each interval. The time is normed to $[-1,1)$ in each interval.

    The total parameter count is $(N+1)M$, where $N$ is the polynmial degree and $M$ the number of intervals with the parameter names *:*:legendrePolynomial.n<degree>:<interval>.

    Oscillation

    A time variable function is given by a oscillation \\[ f(x,t) = f^c(\\M x)\\cos(\\omega_i(t)) + f^s(\\M x)\\sin(\\omega_i(t)) \\]with $\\omega_i=\\frac{2\\pi}{T_i}(t-t_0)$, $t_0$ is timeStart and $T$ is timePeriod in days.

    The parameter names are *:*:oscillation.cos(2*pi/<period(days)>*(t-<timeStart>)):* and *:*:oscillation.sin(2*pi/<period(days)>*(t-<timeStart>)):*.

    Fourier

    A time variable function is given by a fourier expansion \\[ f(x,t) = \\sum_{m=1}^M f_m^c(\\M x)\\cos(2\\pi m \\tau) + f_m^s(\\M x)\\sin(2\\pi m \\tau) \\]with the normalized time \\[ \\tau = \\frac{t-t_A}{t_B-t_A}, \\]and $t_A$ is timeStart, $t_B$ is timeEnd in each interval and $M$ is the fourierDegree.

    The total parameter count is $2MN$, where $N$ is the number of intervals. The parameters are sorted in following order: $f_1^c, f_1^s, f_2^c, \\ldots$ with the parameter names *:*:fourier.cos(<m>*x):<interval> and *:*:fourier.sin(<m>*x):<interval>.

    DoodsonHarmonic

    The time variable function is given by a fourier expansion \\[ f(x,t) = \\sum_{i} f_i^c(x)\\cos(\\Theta_i(t)) + f_i^s(x)\\sin(\\Theta_i(t)), \\]where $\\Theta_i(t)$ are the arguments of the tide constituents $i$ \\[ \\Theta_i(t) = \\sum_{k=1}^6 n_i^k\\beta_k(t), \\]where $\\beta_k(t)$ are the Doodson\'s fundamental arguments ($\\tau,s,h,p,N\',p_s$) and $n_i^k$ are the Doodson multipliers for the term at frequency $i$. The multipliers must be given by doodson coded as Doodson number (e.g. 255.555) or as names intoduced by Darwin (e.g. M2).

    The major constituents given by doodson can be used to interpolate minor tidal constituents using the file inputfileAdmittance. This file can be created with DoodsonHarmonicsCalculateAdmittance.

    The total parameter count is $2N$ with $N$ the number of doodson frequencies. The parameters are sorted in following order: $f_1^c, f_1^s, f_2^c, \\ldots$ with the parameter names *:*:doodson.cos(<doodsonName>):* and *:*:doodson.sin(<doodsonName>):*.'}, 'planetType': { 'name': 'planetType', 'key': 'planetType', 'description': 'Defines the planet to compute the .', 'config_table': 'planetType choice planet earth sun moon mercury venus mars jupiter saturn uranus neptune pluto solarBaryCenter earthMoonBaryCenter', 'display_text': 'Defines the planet to compute the ephemeris.'}, -'platformSelectorType': { 'name': 'platformSelectorType', 'key': 'platformSelectorType', 'description': 'Select a list of platforms (stations, satellites, ...). In a first step all platforms are selected if first selector exclude s platforms otherwise all platforms excluded. When every selector from top to bottom selects or deselects (with exclude ) the matching platforms. See also GnssProcessing . Select all platforms. Select all receivers/transmitters which match the name , markerName , and markerNumber . Select receivers/transmitters from each row of . Additional columns in a row represent alternatives if previous names are not available (e.g. without observation file). Select all platforms which has the specified equipment in the processed time interval. Deselects all selected receivers/transmitters of .', 'config_table': 'name string wildcards: * and ? markerName string wildcards: * and ?, from platform markerNumber string wildcards: * and ?, from platform exclude boolean deselect matching platforms inputfileStringTable filename list of names with alternatives exclude boolean deselect first matching platforms name string wildcards: * and ? serial string wildcards: * and ? equipmentType choice equipment type all all types gnssAntenna sequence antennas radome string wildcards: * and ? gnssReceiver sequence receivers version string wildcards: * and ? slrStation SLR station slrRetroReflector laser retroreflector satelliteIdentifier sequence satellite identifier cospar string wildcards: * and ? norad string wildcards: * and ? sic string wildcards: * and ? sp3 string wildcards: * and ? other other types exclude boolean deselect matching platforms selector platformSelectorType', 'display_text': 'Select a list of platforms (stations, satellites, ...). In a first step all platforms are selected if first selector excludes platforms otherwise all platforms excluded. When every selector from top to bottom selects or deselects (with exclude) the matching platforms.

    See also GnssProcessing.

    All

    Select all platforms.

    Wildcard

    Select all receivers/transmitters which match the name, markerName, and markerNumber.

    File

    Select receivers/transmitters from each row of inputfileStringTable. Additional columns in a row represent alternatives if previous names are not available (e.g. without observation file).

    Equipment

    Select all platforms which has the specified equipment in the processed time interval.

    Exclude

    Deselects all selected receivers/transmitters of selector.'}, +'platformSelectorType': { 'name': 'platformSelectorType', 'key': 'platformSelectorType', 'description': 'Select a list of platforms (stations, satellites, ...). In a first step all platforms are selected if first selector exclude s platforms otherwise all platforms excluded. When every selector from top to bottom selects or deselects (with exclude ) the matching platforms. See also GnssProcessing or SlrProcessing . Select all platforms. Select all receivers/transmitters which match the name , markerName , and markerNumber . Select receivers/transmitters from each row of . Additional columns in a row represent alternatives if previous names are not available (e.g. without observation file). Select all platforms which has the specified equipment in the processed time interval. Deselects all selected receivers/transmitters of .', 'config_table': 'name string wildcards: * and ? markerName string wildcards: * and ?, from platform markerNumber string wildcards: * and ?, from platform exclude boolean deselect matching platforms inputfileStringTable filename list of names with alternatives exclude boolean deselect first matching platforms name string wildcards: * and ? serial string wildcards: * and ? equipmentType choice equipment type all all types gnssAntenna sequence antennas radome string wildcards: * and ? gnssReceiver sequence receivers version string wildcards: * and ? slrStation SLR station slrRetroReflector laser retroreflector satelliteIdentifier sequence satellite identifier cospar string wildcards: * and ? norad string wildcards: * and ? sic string wildcards: * and ? sp3 string wildcards: * and ? other other types exclude boolean deselect matching platforms selector platformSelectorType', 'display_text': 'Select a list of platforms (stations, satellites, ...). In a first step all platforms are selected if first selector excludes platforms otherwise all platforms excluded. When every selector from top to bottom selects or deselects (with exclude) the matching platforms.

    See also GnssProcessing or SlrProcessing.

    All

    Select all platforms.

    Wildcard

    Select all receivers/transmitters which match the name, markerName, and markerNumber.

    File

    Select receivers/transmitters from each row of inputfileStringTable. Additional columns in a row represent alternatives if previous names are not available (e.g. without observation file).

    Equipment

    Select all platforms which has the specified equipment in the processed time interval.

    Exclude

    Deselects all selected receivers/transmitters of selector.'}, 'plotAxisType': { 'name': 'plotAxisType', 'key': 'plotAxisType', 'description': 'Defines the style of the axes of PlotGraph . General axis for arbitrary input data. The input data are interpreted as MJD (modified Julian date). The unit of the tick spacings should be appenend to the number and can be any of Y (year, plot with 4 digits) y (year, plot with 2 digits) O (month, plot using FORMAT_DATE_MAP ) o (month, plot with 2 digits) U (ISO week, plot using FORMAT_DATE_MAP ) u (ISO week, plot using 2 digits) r (Gregorian week, 7-day stride from start of week TIME_WEEK_START ) K (ISO weekday, plot name of day) D (date, plot using FORMAT_DATE_MAP ) d (day, plot day of month 0-31 or year 1-366, via FORMAT_DATE_MAP ) R (day, same as d, aligned with TIME_WEEK_START ) H (hour, plot using FORMAT_CLOCK_MAP ) h (hour, plot with 2 digits) M (minute, plot using FORMAT_CLOCK_MAP ) m (minute, plot with 2 digits) S (second, plot using FORMAT_CLOCK_MAP ) s (second, plot with 2 digits). A secondary time axis can be added to specify larger intervals (e.g dates of hourly data). Examples: Settings for Fig. : majorTickSpacing = 6H , secondary: majorTickSpacing = 1D . Settings for Fig. : majorTickSpacing = 2d , secondary: majorTickSpacing = 1O , options = FORMAT_DATE_MAP="o yyyy" . Settings for Fig. : majorTickSpacing = 1o , secondary: majorTickSpacing = 1Y , options = FORMAT_DATE_MAP="mm" . Axis with string labels. The coordinate system is based on the label indices (e.g. 0, 1, 2).', 'config_table': 'min double The minimum value of the axis. If no value is given, the minimum scale value is set automatically. max double The maximum value of the axis. If no value is given, the maximum scale value is set automatically. majorTickSpacing double The boundary annotation. minorTickSpacing double The spacing of the frame tick intervals. gridLineSpacing double The spacing of the grid line intervals gridLine plotLineType The style of the grid lines. unit string Naming unit to append to the axis values. label string The description of the axis. logarithmic boolean If set to \'yes\', a logarithmic scale is used for the axis. color plotColorType Setting the color of the axis bars and labels. changeDirection boolean If set to \'yes\', the directions right/up are changed to left/down. min time The minimum value of the time axis. If no value is given, the minimum scale value is set automatically. max time The maximum value of the time axis. If no value is given, the maximum scale value is set automatically. majorTickSpacing string Y: year, o: month minorTickSpacing string D: date, d: day gridLineSpacing string H: clock, h: hour, m: minute, s: second secondary sequence secondary time axis majorTickSpacing string Y: year, o: month minorTickSpacing string D: date, d: day gridLineSpacing string H: clock, h: hour, m: minute, s: second color plotColorType color of axis bars and labels gridLine plotLineType The style of the grid lines. changeDirection boolean right->left / up->down options string adjust date format labels string tick labels (ticks are placed at their index. e.g. 0, 1, ..., 5) min expression minimum value of the axis max expression maximum values of the axis orthogonalLabels boolean labels are oriented orthogonal to axis gridLine plotLineType The style of the grid lines. color plotColorType set the color of the axis and labels changeDirection boolean If set to \'yes\', the directions right/up are changed to left/down.', 'display_text': 'Defines the style of the axes of PlotGraph.

    Standard

    General axis for arbitrary input data.

    Time

    The input data are interpreted as MJD (modified Julian date). The unit of the tick spacings should be appenend to the number and can be any of

    • Y (year, plot with 4 digits)
    • y (year, plot with 2 digits)
    • O (month, plot using FORMAT_DATE_MAP)
    • o (month, plot with 2 digits)
    • U (ISO week, plot using FORMAT_DATE_MAP)
    • u (ISO week, plot using 2 digits)
    • r (Gregorian week, 7-day stride from start of week TIME_WEEK_START)
    • K (ISO weekday, plot name of day)
    • D (date, plot using FORMAT_DATE_MAP)
    • d (day, plot day of month 0-31 or year 1-366, via FORMAT_DATE_MAP)
    • R (day, same as d, aligned with TIME_WEEK_START)
    • H (hour, plot using FORMAT_CLOCK_MAP)
    • h (hour, plot with 2 digits)
    • M (minute, plot using FORMAT_CLOCK_MAP)
    • m (minute, plot with 2 digits)
    • S (second, plot using FORMAT_CLOCK_MAP)
    • s (second, plot with 2 digits).

    A secondary time axis can be added to specify larger intervals (e.g dates of hourly data).

    Examples: Settings for Fig. plotAxisType:plotAxisTime1: majorTickSpacing=6H, secondary: majorTickSpacing=1D.

    Settings for Fig. plotAxisType:plotAxisTime2: majorTickSpacing=2d, secondary: majorTickSpacing=1O, options=FORMAT_DATE_MAP="o yyyy".

    Settings for Fig. plotAxisType:plotAxisTime3: majorTickSpacing=1o, secondary: majorTickSpacing=1Y, options=FORMAT_DATE_MAP="mm".

    Labeled

    Axis with string labels. The coordinate system is based on the label indices (e.g. 0, 1, 2).'}, 'plotColorType': { 'name': 'plotColorType', 'key': 'plotColorType', 'description': 'Selects a color. Used in PlotDegreeAmplitudes , PlotGraph , PlotMap , PlotMatrix , PlotSphericalHarmonicsTriangle .', 'config_table': 'plotColorType choice color black red blue green orange darkred yellow lightgreen gray rgb sequence red uint 0..255 green uint 0..255 blue uint 0..255 grayscale sequence value uint 0..255 namedColor sequence colorName string name after GMT definition cycler sequence index uint pick color based on index expression inputfileColorList filename list of colors as defined by GMT', 'display_text': 'Selects a color. Used in PlotDegreeAmplitudes, PlotGraph, PlotMap, PlotMatrix, PlotSphericalHarmonicsTriangle.

    '}, 'plotColorbarType': { 'name': 'plotColorbarType', 'key': 'plotColorbarType', 'description': 'A colorbar as used in PlotMap , PlotMatrix , PlotSphericalHarmonicsTriangle .', 'config_table': 'plotColorbarType sequence min double max double annotation double boundary annotation unit string appended to axis values label string description of the axis logarithmic boolean use logarithmic scale triangleLeft boolean triangleRight boolean illuminate boolean illuminate vertical boolean plot vertical color bar on the right length double length of colorbar in percent margin double between colorbar and figure [cm] colorTable string name of the color bar reverse boolean reverse direction showColorbar boolean', 'display_text': 'A colorbar as used in PlotMap, PlotMatrix, PlotSphericalHarmonicsTriangle.'}, @@ -376,13 +386,17 @@ var documents = { 'plotSymbolType': { 'name': 'plotSymbolType', 'key': 'plotSymbolType', 'description': 'Plots a symbol as used e.g. in or .', 'config_table': 'plotSymbolType choice symbol circle sequence color plotColorType empty: determined from value size double size of symbol [point] blackContour boolean star sequence color plotColorType empty: determined from value size double size of symbol [point] blackContour boolean cross sequence color plotColorType empty: determined from value size double size of symbol [point] blackContour boolean square sequence color plotColorType empty: determined from value size double size of symbol [point] blackContour boolean triangle sequence color plotColorType empty: determined from value size double size of symbol [point] blackContour boolean diamond sequence color plotColorType empty: determined from value size double size of symbol [point] blackContour boolean dash sequence color plotColorType empty: determined from value size double size of symbol [point] blackContour boolean', 'display_text': 'Plots a symbol as used e.g. in plotGraphLayer:linesAndPoints or plotMapLayer:points.'}, 'podRightSideType': { 'name': 'podRightSideType', 'key': 'podRightSideType', 'description': 'Observation vector for precise orbit data (POD) of equations in a least squares adjustment. The observations are reduced by the effect of and (observed minus computed).', 'config_table': 'podRightSideType sequence inputfileOrbit filename kinematic positions of satellite as observations inputfileAccelerometer filename non-gravitational forces in satellite reference frame forces forcesType', 'display_text': 'Observation vector for precise orbit data (POD) of observation equations in a least squares adjustment. The observations are reduced by the effect of inputfileAccelerometer and forces (observed minus computed).'}, 'sggRightSideType': { 'name': 'sggRightSideType', 'key': 'sggRightSideType', 'description': 'Observation vector for gradiometer data (satellite gravity gradiometry, SGG) of equations in a least squares adjustment. The observations are reduced by an , the effect of , and (observed minus computed). The reference gradiometer data can be precomputed with SimulateGradiometer .', 'config_table': 'sggRightSideType sequence inputfileGradiometer filename observed gravity gradients inputfileReferenceGradiometer filename precomputed gradients at orbit positions referencefield gravityfieldType tides tidesType', 'display_text': 'Observation vector for gradiometer data (satellite gravity gradiometry, SGG) of observation equations in a least squares adjustment. The observations are reduced by an inputfileReferenceGradiometer, the effect of referencefield, and tides (observed minus computed).

    The reference gradiometer data can be precomputed with SimulateGradiometer.'}, +'slrParametrizationType': { 'name': 'slrParametrizationType', 'key': 'slrParametrizationType', 'description': 'This class defines the models and parameters of the linearized observation equations for normal points (see SlrProcessing ) where the left side is the observation vector minus the effects computed from the a priori models. After each least squares adjustment (see ) the a priori parameters are updated The vector can be written with . Any outputfiles defined in the parametrizations are written with . Each parametrization (and possible constraint equations) has a name which enables activating/deactivating the estimation of subsets of with . The a priori model is unaffected and is always reduced. The model for the one way range observations between station and reflector can be described as See also SlrProcessing . A priori tropospheric correction is handled by a model (e.g. Mendes and Pavlis). Additional parameters in for zenith delay can be set up via . These parameters can be soft-constrained using to avoid an unsolvable system of normal equations in case of data gaps. The parameter names are <station>:troposphere:<temporal>:<interval> . The estimation of (reduced) dynamic orbits is formulated as variational equations. It is based on calculated with PreprocessingVariationalEquation . Necessary integrations are performed by integrating a moving interpolation polynomial of degree integrationDegree . The must include at least those parameters that were estimated in PreprocessingVariationalEquationOrbitFit . Additional parameters can be set up to reduce orbit mismodeling. The parameters and parameter names are divided into global <satellite>:<parametrizationAcceleration>:*:* , <satellite>:stochasticPulse.x::<time> , <satellite>:stochasticPulse.y::<time> , <satellite>:stochasticPulse.z::<time> , and arc related parameters <satellite>:arc<no>.<parametrizationAcceleration>:*:* , <satellite>:arc<no>.position0.x:: , <satellite>:arc<no>.position0.y:: , <satellite>:arc<no>.position0.z:: . <satellite>:arc<no>.velocity0.x:: , <satellite>:arc<no>.velocity0.y:: , <satellite>:arc<no>.velocity0.z:: . Estimates a (time depending) gravity field together with at least one . The parametrization of the gravity field can be set with . The parameter names are gravityfield:<parametrization>:*:* . Estimates a static position for all in the terrestrial frame. No-net constraints can be applied for a subset of stations, , with a standard deviation of noNetTranslationSigma and noNetRotationSigma and noNetScaleSigma and noNetScaleSigma . If the template is provided the constraints are applied relatively to these positions. Only stations with an existing position file are considered. Without the constraints are applied towards the apriori values from . As a single corrupted station position can disturb the no-net conditions, the rotation/translation parameters are estimated in a robust least squares adjustment beforehand. The computed weight matrix is used to downweight corrupted stations in the constraint equations. In case you want to align to an ITRF/ILRS reference frame, precise coordinates can be generated with Sinex2StationPositions . The parameter names are <station>:position.x:: , <station>:position.y:: , <station>:position.z:: . Earth rotation parameters (ERPs) can be estimated by defining estimatePole ( , ) and estimateUT1 ( ). Estimating length of day (LOD) with the sign according to IGS conventions requires a negative value in . Constraints on the defined parameters can be added via . An example would be to set up so the parameter is included in the normal equation system . Since cannot be determined by SLR, a hard constraint to its a priori value can then be added. The parameter names are earth:polarMotion.xp:<temporal>:<interval> , earth:polarMotion.yp:<temporal>:<interval> , earth:UT1:<temporal>:<interval> , earth:nutation.X:<temporal>:<interval> , earth:nutation.>:<temporal>:<interval> . A priori station range bias value for all . The provides the mean range biases , but these have been determined using the passive satellites LAGEOS and Etalon and are therefore only suitable for passive satellites and not for active ones. Use SlrSinexDataHandling2Files to convert the range biases from to instrument file . Estimates a constant station range bias in for . The parameter names are <station>:rangeBias:: . A priori satellite range bias value for . Estimates a constant satellite range bias in for . The parameter names a <satellite>:rangeBias:: . A priori station-satellite range bias value between all - pairs. For standard processing this class should be setup twice. Once for the model from José Rodríguez (see SlrComModel2RangeBiasStationSatellite ) and additionally for biases from the converted with SlrSinexDataHandling2Files . Estimates the station-satellite range bias in between all - pairs. The parameter names are <station>.<satellite>:rangeBias:: . A priori time bias value for all . The provides the mean time biases , but these have been determined using the passive satellites LAGEOS and Etalon and are therefore only suitable for passive satellites and not for active ones. Use SlrSinexDataHandling2Files to convert the time biases from to instrument file . Estimates a time bias in for . The parameter names are <station>:timeBias:<temporal>:<interval> . Add a pseudo observation equation (constraint) for each selected where is the bias and is the a priori value of the parameter if relativeToApriori is not set. The standard deviation sigma is used to weight the observation equations. Groups a set of parameters. This class can be used to structure complex parametrizations and has no further effect itself.', 'config_table': 'name string used for parameter selection selectStations platformSelectorType outputfileTroposphere filename columns: MJD, ZHD, ZWD, dry north gradient, wet north gradient, dry east gradient, wet east gradient troposphere troposphereType a priori troposphere model troposphereEstimation parametrizationTemporalType [m] parametrization of zenith delays name string used for parameter selection selectSatellites platformSelectorType outputfileOrbit filename variable {satellite} available outputfileParameters filename variable {satellite} available inputfileVariational filename variable {satellite} available stochasticPulse timeSeriesType [mu/s] parametrization of stochastic pulses parametrizationAcceleration parametrizationAccelerationType orbit force parameters ephemerides ephemeridesType integrationDegree uint integration of forces by polynomial approximation of degree n interpolationDegree uint for orbit interpolation and velocity calculation name string used for parameter selection parametrization parametrizationGravityType name string used for parameter selection selectStations platformSelectorType outputfileGriddedPosition filename delta north east up for all stations outputfilePosition filename variable {station} available, full estimated coordinates (in TRF) nameConstraint string used for parameter selection selectNoNetStations platformSelectorType inputfileNoNetPositions filename variable {station} available, precise coordinates used for no-net constraints (in TRF) noNetTranslationSigma double (0 = unconstrained) sigma [m] for no-net translation constraint on station coordinates noNetRotationSigma double (0 = unconstrained) sigma [m] at Earth\'s surface for no-net rotation constraint on station coordinates noNetScaleSigma double (0 = unconstrained) sigma [m] for no-net scale constraint on station coordinates huber double stations > huber*sigma0 are downweighted in no-net constraint huberPower double stations > huber: sigma=(e/huber)^huberPower*sigma0 name string used for parameter selection outputfileEOP filename EOP time series (mjd, xp, yp, sp, dUT1, LOD, X, Y, S) estimatePole parametrizationTemporalType xp, yp [mas] estimateUT1 parametrizationTemporalType rotation angle [ms] estimateNutation parametrizationTemporalType dX, dY [mas] selectStations platformSelectorType inputfileRangeBias filename variable {station} available name string used for parameter selection selectStations platformSelectorType outputfileRangeBias filename variable {station} available selectSatellites platformSelectorType inputfileRangeBias filename variable {satellite} available name string used for parameter selection selectSatellites platformSelectorType outputfileRangeBias filename variable {satellite} available selectStations platformSelectorType selectSatellites platformSelectorType inputfileRangeBias filename variable {station} and {satellite} available name string used for parameter selection selectStations platformSelectorType selectSatellites platformSelectorType outputfileRangeBias filename variable {station} and {satellite} available selectStations platformSelectorType inputfileTimeBias filename variable {station} available name string used for parameter selection selectStations platformSelectorType estimateTimeBias parametrizationTemporalType [ms] name string parameters parameterSelectorType parameter to constrain sigma double sigma of the constraint (same unit as parameter) bias double constrain all selected parameters towards this value relativeToApriori boolean constrain only dx and not full x=dx+x0 parametrization slrParametrizationType', 'display_text': 'This class defines the models and parameters of the linearized observation equations for normal points (see SlrProcessing) \\[\\label{slrParametrizationType:model} \\M l - \\M f(\\M x_0) = \\left.\\frac{\\partial \\M f(\\M x)}{\\partial \\M x}\\right|_{\\M x_0} \\Delta\\M x + \\M\\epsilon, \\]where the left side is the observation vector minus the effects computed from the a priori models. After each least squares adjustment (see SlrProcessing:processingStep:estimate) the a priori parameters are updated \\[\\label{slrParametrizationType:update} \\M x_0 := \\M x_0 + \\Delta\\hat{\\M x}. \\]The vector $\\M x_0$ can be written with SlrProcessing:processingStep:writeAprioriSolution. Any outputfiles defined in the parametrizations are written with SlrProcessing:processingStep:writeResults.

    Each parametrization (and possible constraint equations) has a name which enables activating/deactivating the estimation of subsets of $\\Delta\\M x$ with SlrProcessing:processingStep:selectParametrizations. The a priori model $\\M f(\\M x_0)$ is unaffected and is always reduced.

    The model for the one way range observations between station $s$ and reflector $r$ can be described as \\[\\label{slrParametrizationType:slrFullModel} \\begin{split} f_s^r(\\M x) &= \\frac{1}{2}\\left(\\left\\lVert \\M r^r(t_{bounce})-\\M r_s(t_{trans}) \\right\\rVert + \\left\\lVert \\M r_s(t_{recv})-\\M r^r(t_{bounce}) \\right\\rVert\\right) \\\\ &+ \\text{troposphere}(t,\\M r_{ss}^r) + \\text{bias}^r + \\text{bias}_s + \\text{bias}_s^r + \\text{other}(\\ldots) + \\epsilon_r^s \\end{split} \\] See also SlrProcessing.

    Troposphere

    A priori tropospheric correction is handled by a troposphere model (e.g. Mendes and Pavlis). Additional parameters in $[m]$ for zenith delay can be set up via troposphereEstimation. These parameters can be soft-constrained using parametrization:constraints to avoid an unsolvable system of normal equations in case of data gaps.

    The parameter names are <station>:troposphere:<temporal>:<interval>.

    DynamicOrbits

    The estimation of (reduced) dynamic orbits is formulated as variational equations. It is based on inputfileVariational calculated with PreprocessingVariationalEquation. Necessary integrations are performed by integrating a moving interpolation polynomial of degree integrationDegree. The parametrizationAcceleration must include at least those parameters that were estimated in PreprocessingVariationalEquationOrbitFit. Additional stochasticPulse parameters can be set up to reduce orbit mismodeling.

    The parameters and parameter names are divided into global

    • <satellite>:<parametrizationAcceleration>:*:*,
    • <satellite>:stochasticPulse.x::<time>,
    • <satellite>:stochasticPulse.y::<time>,
    • <satellite>:stochasticPulse.z::<time>,
    and arc related parameters
    • <satellite>:arc<no>.<parametrizationAcceleration>:*:*,
    • <satellite>:arc<no>.position0.x::,
    • <satellite>:arc<no>.position0.y::,
    • <satellite>:arc<no>.position0.z::.
    • <satellite>:arc<no>.velocity0.x::,
    • <satellite>:arc<no>.velocity0.y::,
    • <satellite>:arc<no>.velocity0.z::.

    GravityField

    Estimates a (time depending) gravity field together with at least one parametrization:dynamicOrbits. The parametrization of the gravity field can be set with parametrization.

    The parameter names are gravityfield:<parametrization>:*:*.

    StaticPositions

    Estimates a static position for all selectReceivers in the terrestrial frame.

    No-net constraints can be applied for a subset of stations, selectNoNetReceivers, with a standard deviation of noNetTranslationSigma and noNetRotationSigma and noNetScaleSigma and noNetScaleSigma. If the template inputfileNoNetPositions is provided the constraints are applied relatively to these positions. Only stations with an existing position file are considered. Without inputfileNoNetPositions the constraints are applied towards the apriori values from SlrProcessing:station. As a single corrupted station position can disturb the no-net conditions, the rotation/translation parameters are estimated in a robust least squares adjustment beforehand. The computed weight matrix is used to downweight corrupted stations in the constraint equations.

    In case you want to align to an ITRF/ILRS reference frame, precise coordinates can be generated with Sinex2StationPositions.

    The parameter names are

    • <station>:position.x::,
    • <station>:position.y::,
    • <station>:position.z::.

    EarthRotation

    Earth rotation parameters (ERPs) can be estimated by defining estimatePole ($x_p$, $y_p$) and estimateUT1 ($dUT1, LOD$).

    Estimating length of day (LOD) with the sign according to IGS conventions requires a negative value in parametrizationTemporal:trend:timeStep.

    Constraints on the defined parameters can be added via parametrization:constraints. An example would be to set up estimateUT1:constant so the $dUT1$ parameter is included in the normal equation system . Since $dUT1$ cannot be determined by SLR, a hard constraint to its a priori value can then be added.

    The parameter names are

    • earth:polarMotion.xp:<temporal>:<interval>,
    • earth:polarMotion.yp:<temporal>:<interval>,
    • earth:UT1:<temporal>:<interval>,
    • earth:nutation.X:<temporal>:<interval>,
    • earth:nutation.>:<temporal>:<interval>.

    RangeBiasStationApriori

    A priori station range bias value for all selectStations. The ILRS provides the mean range biases ILRS Data Handling File, but these have been determined using the passive satellites LAGEOS and Etalon and are therefore only suitable for passive satellites and not for active ones. Use SlrSinexDataHandling2Files to convert the range biases from ILRS Data Handling File to instrument file.

    RangeBiasStation

    Estimates a constant station range bias in $[m]$ for selectStations.

    The parameter names are <station>:rangeBias::.

    RangeBiasSatelliteApriori

    A priori satellite range bias value for selectSatellites.

    RangeBiasSatellite

    Estimates a constant satellite range bias in $[m]$ for selectSatellites.

    The parameter names a <satellite>:rangeBias::.

    RangeBiasStationSatelliteApriori

    A priori station-satellite range bias value between all selectStations - selectSatellites pairs.

    For standard ILRS processing this class should be setup twice. Once for the model from José Rodríguez (see SlrComModel2RangeBiasStationSatellite) and additionally for biases from the ILRS Data Handling File converted with SlrSinexDataHandling2Files.

    RangeBiasStationSatellite

    Estimates the station-satellite range bias in $[m]$ between all selectStations - selectSatellites pairs.

    The parameter names are <station>.<satellite>:rangeBias::.

    TimeBiasApriori

    A priori time bias value for all selectStations. The ILRS provides the mean time biases ILRS Data Handling File, but these have been determined using the passive satellites LAGEOS and Etalon and are therefore only suitable for passive satellites and not for active ones. Use SlrSinexDataHandling2Files to convert the time biases from ILRS Data Handling File to instrument file.

    TimeBias

    Estimates a temporal changing time bias in $[ms]$ for selectStations.

    The parameter names are <station>:timeBias:<temporal>:<interval>.

    Constraints

    Add a pseudo observation equation (constraint) for each selected parameters \\[ b-x_0 = 1 \\cdot dx + \\epsilon, \\]where $b$ is the bias and $x_0$ is the a priori value of the parameter if relativeToApriori is not set. The standard deviation sigma is used to weight the observation equations.

    Group

    Groups a set of parameters. This class can be used to structure complex parametrizations and has no further effect itself.'}, +'slrProcessingStepType': { 'name': 'slrProcessingStepType', 'key': 'slrProcessingStepType', 'description': 'Processing step in SlrProcessing . Processing steps enable a dynamic definition of the consecutive steps performed during any kind of SLR processing. The most common steps are , which performs an iterative least squares adjustment, and , which writes all output files defined in SlrProcessing and is usually the last step. Some steps such as and affect all subsequent steps. In case these steps are used within a step, they only affect the steps within this level. Iterative non-linear least squares adjustment. In every iteration it accumulates the system of normal equations, solves the system and updates the estimated parameters. The estimated parameters serve as a priori values in the next iteration and the following processing steps. Iterates until either every single parameter update (converted to an influence in meter) is below a convergenceThreshold or maxIterationCount is reached. With computeResiduals the observation equations are computed again after each update to compute the observation residuals. The overall standard deviation of a single observation used for the weighting is composed of several factors where the is given by :accuracy. The other factors are estimated iteratively from the residuals. With computeWeights a standardized variance for each residual is computed taking the redundancy into account. If is above a threshold huber the observation gets a higher standard deviation used for weighting according to similar to robust least squares adjustment . With adjustSigma0 an individual variance factor can be computed for each station separately In this step all outputfiles defined in are written. It considers the settings of and . It is usually the last processing step, but can also be used at other points in the processing in combination with suffix to write intermediate results. Accumulates the normal equations matrix and writes it. If is set only the selected parameters are written to the normal equations and all other parameters are eliminated beforehand (implicitly solved). The solution of the normals would results in (see ). To write the appropriate apriori vector use . Writes the current apriori vector (see ). If is set only the selected parameters are written. Writes the observation residuals for all . For for each station-satellite pair a file is written. The file name is interpreted as a template with the variables {station} and {satellite} being replaced by the station name. Writes a list of stations (stations) which are used in the last step and selected by . Writes a list of satellites which are used in the last step and selected by . Print residual statistics. station sigma redundancy obsCount outlier ---------------------------------------------- 1874 0.52 0.86 22 1 (4.55 1889 1.20 0.98 186 5 (2.69 1890 0.63 0.77 14 1 (7.14 1891 0.49 0.50 6 0 (0.00 7237 1.08 0.95 236 14 (5.93 7394 0.36 0.88 26 0 (0.00 7811 0.38 0.41 5 0 (0.00 7819 1.21 0.94 120 1 (0.83 7821 0.69 0.95 202 3 (1.49 7827 0.40 0.85 29 1 (3.45 7839 0.52 0.93 143 10 (6.99 7840 0.15 0.80 16 0 (0.00 7841 0.26 0.90 56 1 (1.79 7941 0.55 0.92 277 5 (1.81 8834 0.66 0.88 101 1 (0.99 ---------------------------------------------- satellite sigma redundancy obsCount outlier ---------------------------------------------- lageos1 1.04 0.94 722 24 (3.32 lageos2 0.91 0.95 590 11 (1.86 etalon1 1.19 0.78 57 2 (3.51 etalon2 1.10 0.81 70 6 (8.57 ---------------------------------------------- Enable/disable parameter groups and constraint groups for subsequent steps, e.g. or . The name and nameConstraint of these groups are defined in . Prior models or previously estimated parameters used as new apriori values are unaffected and they are always reduced from the observations. This means all unselected parameters are kept fixed to their last result. This step can be used to process only a subset of satellites in subsequent processing steps. This step can be used to process only a subset of stations in subsequent processing steps. Perform these processing steps. This step can be used to structure complex processing flows. The processing steps defined within a group only affect the steps within this group.', 'config_table': 'computeResiduals boolean adjustSigma0 boolean adjust sigma0 by scale factor (per station) computeWeights boolean downweight outliers huber double residuals > huber*sigma0 are downweighted huberPower double residuals > huber: sigma=(e/huber)^huberPower*sigma0 convergenceThreshold double [m] stop iteration once full convergence is reached maxIterationCount uint maximum number of iterations suffix string appended to every output file name (e.g. orbit.G01.suffix.dat) outputfileNormalEquations filename normals remainingParameters parameterSelectorType parameter order/selection of output normal equations constraintsOnly boolean write only normals of constraints without observations defaultNormalsBlockSize uint block size for distributing the normal equations, 0: one block, empty: original block size outputfileAprioriSolution filename a priori parameters outputfileParameterNames filename parameter names remainingParameters parameterSelectorType parameter order/selection of output normal equations selectStations platformSelectorType subset of used stations selectSatellites platformSelectorType subset of used satellites outputfileResiduals filename variable {station} available selectStations platformSelectorType subset of used stations outputfileUsedStationList filename ascii file with names of used stations selectSatellites platformSelectorType subset of used satellites outputfileUsedSatelliteList filename ascii file with names parametrization choice enable sequence name string wildcards: * and ? disable sequence name string wildcards: * and ? selectSatellites platformSelectorType selectStations platformSelectorType processingStep slrProcessingStepType steps are processed consecutively', 'display_text': 'Processing step in SlrProcessing.

    Processing steps enable a dynamic definition of the consecutive steps performed during any kind of SLR processing. The most common steps are estimate, which performs an iterative least squares adjustment, and writeResults, which writes all output files defined in SlrProcessing and is usually the last step. Some steps such as selectParametrizations and selectStations affect all subsequent steps. In case these steps are used within a group step, they only affect the steps within this level.

    Estimate

    Iterative non-linear least squares adjustment. In every iteration it accumulates the system of normal equations, solves the system and updates the estimated parameters. The estimated parameters serve as a priori values in the next iteration and the following processing steps. Iterates until either every single parameter update (converted to an influence in meter) is below a convergenceThreshold or maxIterationCount is reached.

    With computeResiduals the observation equations are computed again after each update to compute the observation residuals.

    The overall standard deviation of a single observation used for the weighting is composed of several factors \\[ \\hat{\\sigma}_i = \\hat{\\sigma}_i^{huber} \\hat{\\sigma}^{stat} \\sigma_{apriori}^{stat}, \\]where the $\\sigma_{apriori}^{stat}$ is given by station:accuracy. The other factors are estimated iteratively from the residuals.

    With computeWeights a standardized variance $\\hat{s}_i^2$ for each residual $\\hat{\\epsilon}_i$ is computed \\[ \\hat{s}_i^2 = \\frac{1}{\\hat{\\sigma}^{stat} \\sigma_{apriori}^{stat}}\\frac{\\hat{\\epsilon}_i^2}{r_i} \\qquad\\text{with}\\qquad r_i = \\left(\\M A\\left(\\M A^T\\M A\\right)^{-1}\\M A^T\\right)_{ii} \\]taking the redundancy $r_i$ into account. If $\\hat{s}_i$ is above a threshold huber the observation gets a higher standard deviation used for weighting according to \\[ \\hat{\\sigma}_i^{huber} = \\left\\{ \\begin{array}{ll} 1 & s < huber,\\\\ (\\hat{s}_i/huber)^{huberPower} & s \\ge huber \\end{array} \\right., \\]similar to robust least squares adjustment.

    With adjustSigma0 an individual variance factor can be computed for each station separately \\[ \\hat{\\sigma}^{stat} = \\sqrt{\\frac{\\hat{\\M\\epsilon}^T\\M P\\hat{\\M\\epsilon}}{r}}. \\]

    WriteResults

    In this step all outputfiles defined in parametrizations are written. It considers the settings of processingStep:selectParametrizations and processingStep:selectStations.

    It is usually the last processing step, but can also be used at other points in the processing in combination with suffix to write intermediate results.

    WriteNormalEquations

    Accumulates the normal equations matrix and writes it. If remainingParameters is set only the selected parameters are written to the normal equations and all other parameters are eliminated beforehand (implicitly solved).

    The solution of the normals would results in $\\Delta\\M x$ (see parametrizations). To write the appropriate apriori vector $\\M x_0$ use processingStep:writeAprioriSolution.

    WriteAprioriSolution

    Writes the current apriori vector $\\M x_0$ (see parametrizations). If remainingParameters is set only the selected parameters are written.

    WriteResiduals

    Writes the observation residuals for all selectStations. For for each station-satellite pair a file is written. The file name is interpreted as a template with the variables {station} and {satellite} being replaced by the station name.

    WriteUsedStationList

    Writes a list of stations (stations) which are used in the last step and selected by selectStations.

    WriteUsedSatelliteList

    Writes a list of satellites which are used in the last step and selected by selectSatellites.

    PrintResidualStatistics

    Print residual statistics.

       station   sigma redundancy obsCount outlier   ----------------------------------------------   1874       0.52   0.86      22      1 (4.55    1889       1.20   0.98     186      5 (2.69    1890       0.63   0.77      14      1 (7.14    1891       0.49   0.50       6      0 (0.00    7237       1.08   0.95     236     14 (5.93    7394       0.36   0.88      26      0 (0.00    7811       0.38   0.41       5      0 (0.00    7819       1.21   0.94     120      1 (0.83    7821       0.69   0.95     202      3 (1.49    7827       0.40   0.85      29      1 (3.45    7839       0.52   0.93     143     10 (6.99    7840       0.15   0.80      16      0 (0.00    7841       0.26   0.90      56      1 (1.79    7941       0.55   0.92     277      5 (1.81    8834       0.66   0.88     101      1 (0.99    ----------------------------------------------   satellite sigma redundancy obsCount outlier   ----------------------------------------------   lageos1    1.04   0.94     722     24 (3.32    lageos2    0.91   0.95     590     11 (1.86    etalon1    1.19   0.78      57      2 (3.51    etalon2    1.10   0.81      70      6 (8.57    ---------------------------------------------- 

    SelectParametrizations

    Enable/disable parameter groups and constraint groups for subsequent steps, e.g. processingStep:estimate or processingStep:writeResults. The name and nameConstraint of these groups are defined in parametrizations. Prior models or previously estimated parameters used as new apriori $\\M x_0$ values are unaffected and they are always reduced from the observations. This means all unselected parameters are kept fixed to their last result.

    SelectSatellites

    This step can be used to process only a subset of satellites in subsequent processing steps.

    SelectStations

    This step can be used to process only a subset of stations in subsequent processing steps.

    Group

    Perform these processing steps. This step can be used to structure complex processing flows. The select.. processing steps defined within a group only affect the steps within this group.'}, +'slrSatelliteGeneratorType': { 'name': 'slrSatelliteGeneratorType', 'key': 'slrSatelliteGeneratorType', 'description': 'Definition and basic information of SLR satellites. See also SlrProcessing . A list of satellite names must be provided via . The other input files are read for each satellite, where the file name is interpreted as a template with the variable {satellite} being replaced by the satellite name from list. The contains information about laser retro-reflector, optical reference point, retro-reflector orientation, range corrections and center of mass. It can be created via PlatformCreate . If ist not provided an orbit reference frame (along, cross, nearly nadir) is assumed.', 'config_table': 'inputfileSatelliteList filename ascii file with satellite names, used to loop variable {satellite} inputfileSatelliteInfo filename variable {satellite} available inputfileOrbit filename variable {satellite} available inputfileAttitude filename variable {satellite} available interpolationDegree uint for orbit interpolation and velocity calculation', 'display_text': 'Definition and basic information of SLR satellites.

    See also SlrProcessing.

    Satellites

    A list of satellite names must be provided via inputfileSatelliteList. The other input files are read for each satellite, where the file name is interpreted as a template with the variable {satellite} being replaced by the satellite name from list. The inputfileSatelliteInfo contains information about laser retro-reflector, optical reference point, retro-reflector orientation, range corrections and center of mass. It can be created via PlatformCreate. If inputfileAttitude ist not provided an orbit reference frame (along, cross, nearly nadir) is assumed.'}, +'slrStationGeneratorType': { 'name': 'slrStationGeneratorType', 'key': 'slrStationGeneratorType', 'description': 'Definition and basic information of SLR ground stations. See also SlrProcessing . A list of station names must be provided via . It defines the variable {station} for the station specific input files. The contains metadata information like station number, station name and approximate station postion in terrestrial reference frame (TRF) considering the station eccentricities. They can be created via SinexEccentricties2SlrPlatform or PlatformCreate . The are separate files for each {station} - {satellite} pair. They can be converted from CRD format via Crd2NormalPoints , CSTG format via Cstg2NormalPoints and MERIT II format via Merit2NormalPoints and Merit2FullRate . The apriori observation weighting is defined by the expression accuracy in . The following variables are defined for each observation from the : {residual} , {accuracy} , {redundancy} , {laserWavelength} , {azimut} , {elevation} . Observations with non-positive accuracies are removed. This can be used for a rough outlier removal by an expression such as accuracy = if(abs(residual)>30, NAN, accuracy) . The effects of loading and tidal deformation on station positions can be corrected for via and , respectively. Tidal deformations typically include: : Earth tidal deformations (IERS conventions) : ocean tidal deformations (e.g. fes2014b n720, minDegree = 1 ) : atmospheric tidal deformation (e.g. AOD1B RL06, minDegree = 1 ) : pole tidal deformations (IERS conventions) : ocean pole tidal deformations (IERS conventions)', 'config_table': 'inputfileStationList filename ascii file with station names inputfileStationInfo filename station metadata inputfileStationPosition filename station position inputfileObservations filename variable {station} {satellite} available accuracy expression [m] used for weighting, variables: {residual}, {accuracy}, {redundancy}, {laserWavelength}, {azimut}, {elevation} loadingDisplacement gravityfieldType loading deformation tidalDisplacement tidesType tidal deformation ephemerides ephemeridesType for tidal deformation inputfileDeformationLoadLoveNumber filename inputfilePotentialLoadLoveNumber filename if full potential is given and not only loading potential elevationCutOff angle [degree] ignore observations below cutoff interpolationDegree uint for position interpolation', 'display_text': 'Definition and basic information of SLR ground stations.

    See also SlrProcessing.

    Stations

    A list of station names must be provided via inputfileStationList. It defines the variable {station} for the station specific input files. The inputfileStationInfo contains metadata information like station number, station name and approximate station postion in terrestrial reference frame (TRF) considering the station eccentricities. They can be created via SinexEccentricties2SlrPlatform or PlatformCreate. The inputfileObservations are separate files for each {station}-{satellite} pair. They can be converted from CRD format via Crd2NormalPoints, CSTG format via Cstg2NormalPoints and MERIT II format via Merit2NormalPoints and Merit2FullRate.

    The apriori observation weighting is defined by the expression accuracy in $[m]$. The following variables are defined for each observation from the inputfileObservations: {residual}, {accuracy}, {redundancy}, {laserWavelength}, {azimut}, {elevation}. Observations with non-positive accuracies are removed. This can be used for a rough outlier removal by an expression such as accuracy = if(abs(residual)>30, NAN, accuracy).

    The effects of loading and tidal deformation on station positions can be corrected for via loadingDisplacement and tidalDisplacement, respectively. Tidal deformations typically include:

    '}, 'sphericalHarmonicsFilterType': { 'name': 'sphericalHarmonicsFilterType', 'key': 'sphericalHarmonicsFilterType', 'description': 'Filtering of a spherical harmonics expansion. Orderwise filtering with the DDK filter by Kusche et al. 2009. Filtering the spherical harmonics expansion with a Gaussian filter. radius gives the filter radius on the Earth surface in km. Filtering the spherical harmonics expansion with a matrix filter.', 'config_table': 'level uint DDK filter level (1, 2, 3, ..., 8) inputfileNormalEquation filename radius double filter radius [km] inputfileMatrix filename minDegree uint of matrix maxDegree uint of matrix numbering sphericalHarmonicsNumberingType numbering scheme of the matrix', 'display_text': 'Filtering of a spherical harmonics expansion.

    DDK

    Orderwise filtering with the DDK filter by Kusche et al. 2009.

    Gauss

    Filtering the spherical harmonics expansion with a Gaussian filter. radius gives the filter radius on the Earth surface in km.

    Matrix

    Filtering the spherical harmonics expansion with a matrix filter.'}, 'sphericalHarmonicsNumberingType': { 'name': 'sphericalHarmonicsNumberingType', 'key': 'sphericalHarmonicsNumberingType', 'description': 'This class organizes the numbering scheme of spherical harmonics coefficients in a parameter vector (e.g Gravityfield2SphericalHarmonicsVector and the design matrix of . Numbering degree by degree: Numbering order by order: Numbering order by order with cnm, snm non-alternating: Numbering as specified in the chosen file. The is a matrix with the first column indicating cnm/snm with 0 or 1. The second and third column specify degree and order.', 'config_table': 'inputfile filename', 'display_text': 'This class organizes the numbering scheme of spherical harmonics coefficients in a parameter vector (e.g Gravityfield2SphericalHarmonicsVector and the design matrix of parametrizationGravity:sphericalHarmoncis.

    Degree

    Numbering degree by degree: \\[ c20, c21, s21, c22, s22, c30, c31, s31, c32, s32,\\ldots \\]

    Order

    Numbering order by order: \\[ c20, c30, c40, \\ldots, c21, s21, c31, s31, \\ldots, c22, s22 \\]

    OrderNonAlternating

    Numbering order by order with cnm, snm non-alternating: \\[ c20, c30, c40, \\ldots, c21, c31, c41, \\ldots, s21, s31, s41, \\]

    File

    Numbering as specified in the chosen file. The inputfile is a matrix with the first column indicating cnm/snm with 0 or 1. The second and third column specify degree and order.'}, 'sstRightSideType': { 'name': 'sstRightSideType', 'key': 'sstRightSideType', 'description': 'Observation vector for GRACE like data (satellite-tracking and precise orbit data (POD)) of equations in a least squares adjustment. The observations are reduced by the effect of and (observed minus computed).', 'config_table': 'sstRightSideType sequence inputfileSatelliteTracking filename ranging observations and corrections inputfileOrbit1 filename kinematic positions of satellite A as observations inputfileOrbit2 filename kinematic positions of satellite B as observations inputfileAccelerometer1 filename non-gravitational forces in satellite reference frame A inputfileAccelerometer2 filename non-gravitational forces in satellite reference frame B forces forcesType', 'display_text': 'Observation vector for GRACE like data (satellite-tracking and precise orbit data (POD)) of observation equations in a least squares adjustment. The observations are reduced by the effect of inputfileAccelerometer and forces (observed minus computed).'}, 'thermosphereType': { 'name': 'thermosphereType', 'key': 'thermosphereType', 'description': 'This class provides functions for calculating the density, temperature and velocity in the thermosphere. The wind is computed by HWM14 model if hwm14DataDirectory is provided. A quiet thermosphere is assumed if inputfileMagnetic3hAp is not given. Thermosphere parameters from the JB2008 model: Bowman, B. R., Tobiska, W. K., Marcos, F. A., Huang, C. Y., Lin, C. S., Burke, W. J. (2008). A new empirical thermospheric density model JB2008 using new solar and geomagnetic indices. In AIAA/AAS Astrodynamics Specialist Conference and Exhibit. https://doi.org/10.2514/6.2008-6438 Thermosphere parameters from the NRLMSIS2 model: Emmert J.D, D.P.Drob, J.M. Picone, et al. (2020), NRLMSIS 2.0: A whole-atmosphere empirical model of temperature and neutral species densities. Earth and Space Science, Volume 8, 3 https://doi.org/10.1029/2020EA001321', 'config_table': 'inputfileSolfsmy filename solar indices inputfileDtc filename inputfileMagnetic3hAp filename indicies for wind model hwm14DataDirectory filename directory containing dwm07b104i.dat, gd2qd.dat, hwm123114.bin inputfileMsis filename input NRLMSIS 2.0 inputfileModelParameters filename path to msis20.parm file inputfileMagnetic3hAp filename indicies for wind model hwm14DataDirectory filename directory containing dwm07b104i.dat, gd2qd.dat, hwm123114.bin', 'display_text': 'This class provides functions for calculating the density, temperature and velocity in the thermosphere. The wind is computed by HWM14 model if hwm14DataDirectory is provided. A quiet thermosphere is assumed if inputfileMagnetic3hAp is not given.

    JB2008

    Thermosphere parameters from the JB2008 model:

    Bowman, B. R., Tobiska, W. K., Marcos, F. A., Huang, C. Y., Lin, C. S., Burke, W. J. (2008). A new empirical thermospheric density model JB2008 using new solar and geomagnetic indices. In AIAA/AAS Astrodynamics Specialist Conference and Exhibit. https://doi.org/10.2514/6.2008-6438

    NRLMSIS2

    Thermosphere parameters from the NRLMSIS2 model:

    Emmert J.D, D.P.Drob, J.M. Picone, et al. (2020), NRLMSIS 2.0: A whole-atmosphere empirical model of temperature and neutral species densities. Earth and Space Science, Volume 8, 3 https://doi.org/10.1029/2020EA001321'}, 'tidesType': { 'name': 'tidesType', 'key': 'tidesType', 'description': 'This class computes functionals of the time depending tide potential, e.g potential, acceleration or gravity gradients. If several instances of the class are given the results are summed up. Before summation every single result is multiplicated by a factor . To get the difference between two ocean tide models you must choose one factor by 1 and the other by -1. To get the mean of two models just set each factor to 0.5. This class computes the tide generating potential (TGP) of sun, moon and planets (Mercury, Venus, Mars, Jupiter, Saturn). It takes into account the flattening of the Earth (At the moment only at the acceleration level). The computed result is multiplied with factor . This class computes the earth tide according to the IERS2003 conventions. The values of solid Earth tide external potential Love numbers and the frequency dependent corrections of these values are given in the file . The effect of the permanent tide is removed if includePermanentTide is set to false. The computed result is multiplied with factor . The potential coefficients of the solid Earth pole tide according to the IERS2003 conventions are given by with is the scale , is the outPhase and are the wobble variables in seconds of arc. They are related to the polar motion variables according to The mean pole is approximated by a polynomial read from . The displacment is calculated with where is the horizontalDisplacement and is the verticalDisplacement . The computed result is multiplied with factor . The ocean pole tide is generated by the centrifugal effect of polar motion on the oceans. The potential coefficients of this effect is given by IERS2003 conventions are given by where the coefficients are read from file , is given by gammaReal and gammaImaginary and are the wobble variables in radians. They are related to the polar motion variables according to The mean pole is approximated by a polynomial read from . The computed result is multiplied with factor . The time variable potential of ocean tides is given by a fourier expansion where and are spherical harmonics expansions and are read from the file . If set the expansion is limited in the range between minDegree and maxDegree inclusivly. are the arguments of the tide constituents : where are the Doodson\'s fundamental arguments ( ) and are the Doodson multipliers for the term at frequency . The major constituents given by can be used to interpolate minor tidal constituents using the file . This file can be created with DoodsonHarmonicsCalculateAdmittance . After the interpolation step a selection of the computed constituents can be choosen by . Only these constiuents are considered for the results. If no is set all constituents will be used. The constituents can be coded as Doodson number (e.g. 255.555) or as names intoduced by Darwin (e.g. M2). The computed result is multiplied with factor . Computes the centrifugal potential in a rotating system The current rotation vector is computed from the provided by the calling program. The computed result is multiplied with factor . Be careful, the centrifugal potential is not harmonic. Convolution with a harmonic kernel (e.g. to compute gravity anomalies) is not meaningful. This class computes the solid moon tide according to the IERS2010 conventions. The values of solid Moon tide external potential Love numbers are given and there are no frequency dependent corrections of these values. The computed result is multiplied with factor . Groups a set of and has no further effect itself.', 'config_table': 'useMoon boolean TGP of moon useSun boolean TGP of sun usePlanets boolean TGP of planets useEarth boolean TGP of Earth c20Earth double J2 flattening of the Earth factor double the result is multiplied by this factor, set -1 to subtract the field inputfileEarthtide filename includePermanentTide boolean results in FALSE: zero tide, TRUE: tide free gravity field factor double the result is multiplied by this factor, set -1 to subtract the field scale double outPhase double inputfileMeanPole filename horizontalDisplacement double [m] verticalDisplacement double [m] factor double the result is multiplied by this factor, set -1 to subtract the field inputfileOceanPole filename minDegree uint maxDegree uint gammaReal double gammaImaginary double inputfileMeanPole filename factor double the result is multiplied by this factor, set -1 to subtract the field inputfileTides filename inputfileAdmittance filename interpolation of minor constituents selectDoodson doodson consider only these constituents, code number (e.g. 255.555) or darwin name (e.g. M2) minDegree uint maxDegree uint nodeCorr uint nodal corrections: 0-no corr, 1-IHO, 2-Schureman factor double the result is multiplied by this factor, set -1 to subtract the field factor double the result is multiplied by this factor, set -1 to subtract the field k20 double k30 double factor double the result is multiplied by this factor, set -1 to subtract the field tides tidesType factor double the result is multiplied by this factor', 'display_text': 'This class computes functionals of the time depending tide potential, e.g potential, acceleration or gravity gradients.

    If several instances of the class are given the results are summed up. Before summation every single result is multiplicated by a factor. To get the difference between two ocean tide models you must choose one factor by 1 and the other by -1. To get the mean of two models just set each factor to 0.5.

    AstronomicalTide

    This class computes the tide generating potential (TGP) of sun, moon and planets (Mercury, Venus, Mars, Jupiter, Saturn). It takes into account the flattening of the Earth (At the moment only at the acceleration level).

    The computed result is multiplied with factor.

    EarthTide

    This class computes the earth tide according to the IERS2003 conventions. The values of solid Earth tide external potential Love numbers and the frequency dependent corrections of these values are given in the file inputfileEarthtide. The effect of the permanent tide is removed if includePermanentTide is set to false.

    The computed result is multiplied with factor.

    PoleTide

    The potential coefficients of the solid Earth pole tide according to the IERS2003 conventions are given by \\[ \\begin{split} \\Delta c_{21} &= s\\cdot(m_1 + o\\cdot m_2), \\\\ \\Delta s_{21} &= s\\cdot(m_2 - o\\cdot m_1), \\end{split} \\]with $s$ is the scale, $o$ is the outPhase and $(m_1,m_2)$ are the wobble variables in seconds of arc. They are related to the polar motion variables $(x_p,y_p)$ according to \\[ \\begin{split} m_1 &= (x_p - \\bar{x}_p), \\\\ m_2 &= -(y_p - \\bar{y}_p), \\end{split} \\]The mean pole $(\\bar{x}_p, \\bar{y}_p)$ is approximated by a polynomial read from inputfileMeanPole.

    The displacment is calculated with \\[ \\begin{split} S_r &= -v\\sin2\\vartheta(m_1\\cos\\lambda+m_2\\sin\\lambda),\\\\ S_\\vartheta &= -h\\cos2\\vartheta(m_1\\cos\\lambda+m_2\\sin\\lambda),\\\\ S_\\lambda &= h\\cos\\vartheta(m_1\\sin\\lambda-m_2\\cos\\lambda), \\end{split} \\]where $h$ is the horizontalDisplacement and $v$ is the verticalDisplacement.

    The computed result is multiplied with factor.

    OceanPoleTide

    The ocean pole tide is generated by the centrifugal effect of polar motion on the oceans. The potential coefficients of this effect is given by IERS2003 conventions are given by \\[ \\begin{Bmatrix} \\Delta c_{nm} \\\\ \\Delta s_{nm} \\end{Bmatrix}= \\begin{Bmatrix} c_{nm}^R \\\\ s_{nm}^R \\end{Bmatrix} (m_1\\gamma^R+m_2\\gamma^I)+ \\begin{Bmatrix} c_{nm}^I \\\\ s_{nm}^I \\end{Bmatrix} (m_2\\gamma^R-m_1\\gamma^I) \\]where the coefficients are read from file inputfileOceanPole, $\\gamma=\\gamma^R+i\\gamma^I$ is given by gammaReal and gammaImaginary and $(m_1,m_2)$ are the wobble variables in radians. They are related to the polar motion variables $(x_p,y_p)$ according to \\[ \\begin{split} m_1 &= (x_p - \\bar{x}_p), \\\\ m_2 &= -(y_p - \\bar{y}_p), \\end{split} \\]The mean pole $(\\bar{x}_p, \\bar{y}_p)$ is approximated by a polynomial read from inputfileMeanPole.

    The computed result is multiplied with factor.

    DoodsonHarmonicTide

    The time variable potential of ocean tides is given by a fourier expansion \\[ V(\\M x,t) = \\sum_{f} V_f^c(\\M x)\\cos(\\Theta_f(t)) + V_f^s(\\M x)\\sin(\\Theta_f(t)), \\]where $V_f^c(\\M x)$ and $V_f^s(\\M x)$ are spherical harmonics expansions and are read from the file inputfileDoodsonHarmonic. If set the expansion is limited in the range between minDegree and maxDegree inclusivly. $\\Theta_f(t)$ are the arguments of the tide constituents $f$: \\[ \\Theta_f(t) = \\sum_{i=1}^6 n_f^i\\beta_i(t), \\]where $\\beta_i(t)$ are the Doodson\'s fundamental arguments ($\\tau,s,h,p,N\',p_s$) and $n_f^i$ are the Doodson multipliers for the term at frequency $f$.

    The major constituents given by inputfileDoodsonHarmonic can be used to interpolate minor tidal constituents using the file inputfileAdmittance. This file can be created with DoodsonHarmonicsCalculateAdmittance.

    After the interpolation step a selection of the computed constituents can be choosen by selectDoodson. Only these constiuents are considered for the results. If no selectDoodson is set all constituents will be used. The constituents can be coded as Doodson number (e.g. 255.555) or as names intoduced by Darwin (e.g. M2).

    The computed result is multiplied with factor.

    Centrifugal

    Computes the centrifugal potential in a rotating system \\[ V(\\M r, t) = \\frac{1}{2} (\\M\\omega(t)\\times\\M r)^2. \\]The current rotation vector $\\M\\omega(t)$ is computed from the earthRotation provided by the calling program. The computed result is multiplied with factor.

    Be careful, the centrifugal potential is not harmonic. Convolution with a harmonic kernel (e.g. to compute gravity anomalies) is not meaningful.

    SolidMoonTide

    This class computes the solid moon tide according to the IERS2010 conventions. The values of solid Moon tide external potential Love numbers are given and there are no frequency dependent corrections of these values. The computed result is multiplied with factor.

    Group

    Groups a set of tides and has no further effect itself.'}, 'timeSeriesType': { 'name': 'timeSeriesType', 'key': 'timeSeriesType', 'description': 'This class generates a series of points in time. The series is always sorted in ascending order. Depending of the application the series is interpreted as list of points or as intervals between the points. Generates a time series with uniform sampling. The first point in time will be timeStart . The last generated point in time will be less or equal timeEnd . The time step between generated points in time is given by sampling . Generates a time series with uniform sampling between timeStart and timeEnd . intervallCount gives the count of intervals. This class generates count+1 points in time inclusive timeStart and timeEnd . The points of the time series are given explicitly with time . If monthMiddle is set, time points are generated at mid of each month inclusively the monthStart in yearStart and monthEnd in yearEnd . Otherwise times are given at the first of each month and a time point after the last month. If yearMiddle is set, time points are generated at mid of each year inclusively yearStart and yearEnd . Otherwise times are given at the first of each year and a time point after the last year. Generates a time series with monthly sampling. The first point in time will be timeStart and the following points are generated for each month at the same day and time in month. The last generated point in time will be less or equal timeEnd . Generates a time series with yearly sampling. The first point in time will be timeStart and the following points are generated for each year at the same day and time in year. The last generated point in time will be less or equal timeEnd . Read a time series (epochs) from an instrument file . The time series can be restricted to the interval starting from timeStart and before timeEnd . Reconstruct a time series from an instrument file . The time series is the first epoch of each arc plus one time step beyond the last epoch of the last arc (using median sampling). Reads an orbit file and create a time stamp for each ascending equator crossing. The time series can be restricted to the interval starting from timeStart and before timeEnd . In a first step a is generated. In a second step all times are removed which are in range before or after excludeMargin seconds of the times given by . Only times for which the is met are included in the time series. The variableLoopTime is set to every time and the is evaluated. Interpolates nodeInterpolation count points between the given uniformly.', 'config_table': 'timeStart time first point in time timeEnd time last point in time will be less or equal timeEnd sampling time time step between points in time timeStart time 1st point of the time series timeEnd time last point of the time series intervalCount uint count of intervals, count+1 points in time will generated time time explicit list of points in time monthStart uint yearStart uint monthEnd uint yearEnd uint useMonthMiddle boolean time points are mid of months, otherwise the 1st of each month + a time point behind the last month yearStart uint yearEnd uint useYearMiddle boolean time points are mid of years, otherwise the 1st of each year + a time point behind the last year timeStart time first point in time timeEnd time last point in time will be less or equal timeEnd timeStart time first point in time timeEnd time last point in time will be less or equal timeEnd inputfileInstrument filename timeStart time exclude peochs before this epoch timeEnd time only epochs before this time are used inputfileInstrument filename Must be regular. Time series is first epoch of each arc plus one time step extrapolated from last epoch of last arc. inputfileOrbit filename timeStart time exclude peochs before this epoch timeEnd time only epochs before this time are used timeSeries timeSeriesType time series to be created timeSeriesExclude timeSeriesType exclude this time points from time series (within margin) excludeMargin double on both sides [seconds] timeSeries timeSeriesType only times for which condition is met will be included variableLoopTime string variable with time of each loop condition conditionType test for each time timeSeries timeSeriesType time series to be created nodeInterpolation uint interpolates count points in each time interval given by the time series', 'display_text': 'This class generates a series of points in time. The series is always sorted in ascending order. Depending of the application the series is interpreted as list of points or as intervals between the points.

    UniformSampling

    Generates a time series with uniform sampling. The first point in time will be timeStart. The last generated point in time will be less or equal timeEnd. The time step between generated points in time is given by sampling.

    UniformInterval

    Generates a time series with uniform sampling between timeStart and timeEnd. intervallCount gives the count of intervals. This class generates count+1 points in time inclusive timeStart and timeEnd.

    Irregular

    The points of the time series are given explicitly with time.

    Monthly

    If monthMiddle is set, time points are generated at mid of each month inclusively the monthStart in yearStart and monthEnd in yearEnd. Otherwise times are given at the first of each month and a time point after the last month.

    Yearly

    If yearMiddle is set, time points are generated at mid of each year inclusively yearStart and yearEnd. Otherwise times are given at the first of each year and a time point after the last year.

    EveryMonth

    Generates a time series with monthly sampling. The first point in time will be timeStart and the following points are generated for each month at the same day and time in month. The last generated point in time will be less or equal timeEnd.

    EveryYear

    Generates a time series with yearly sampling. The first point in time will be timeStart and the following points are generated for each year at the same day and time in year. The last generated point in time will be less or equal timeEnd.

    Instrument

    Read a time series (epochs) from an instrument file. The time series can be restricted to the interval starting from timeStart and before timeEnd.

    InstrumentArcIntervals

    Reconstruct a time series from an instrument file. The time series is the first epoch of each arc plus one time step beyond the last epoch of the last arc (using median sampling).

    Revolution

    Reads an orbit file and create a time stamp for each ascending equator crossing. The time series can be restricted to the interval starting from timeStart and before timeEnd.

    Exclude

    In a first step a timeSeries is generated. In a second step all times are removed which are in range before or after excludeMargin seconds of the times given by timeSeriesExclude.

    Conditional

    Only times for which the condition is met are included in the time series. The variableLoopTime is set to every time and the condition is evaluated.

    Interpolate

    Interpolates nodeInterpolation count points between the given timeSeries uniformly.'}, -'troposphereType': { 'name': 'troposphereType', 'key': 'troposphereType', 'description': 'This class provides functions for calculating and estimating the signal delay in the dry and wet atmosphere. Tropospheric delays based on the Vienna Mapping Functions 3 (VMF3) model (Landskron and Boehm 2017, DOI: ). Hydrostatic and wet mapping function coefficients ( , ) and zenith delays (ZHD, ZWD) have to be provided via . This file can contain either station-specific data (see ViennaMappingFunctionStation2File ) or data on a regular global grid (see ViennaMappingFunctionGrid2File ). In the second case mapping coefficients and zenith delays are interpolated to the requested coordinates. This includes a height correction that requires approximate meteorological data provided via . Tropospheric delays based on the Global Pressure and Temperature 3 (GPT3) model (Landskron and Boehm 2017, DOI: ). It is an empirical model derived from the Vienna Mapping Functions 3 (VMF3, see ) and thus does not require additional mapping coefficients and zenith delay values.', 'config_table': 'inputfileVmfCoefficients filename ah, aw, zhd, zwd coefficients inputfileGpt filename gridded GPT data aHeight double parameter a (height correction) bHeight double parameter b (height correction) cHeight double parameter c (height correction) inputfileGpt filename gridded GPT data aHeight double parameter a (height correction) bHeight double parameter b (height correction) cHeight double parameter c (height correction)', 'display_text': 'This class provides functions for calculating and estimating the signal delay in the dry and wet atmosphere.

    ViennaMapping

    Tropospheric delays based on the Vienna Mapping Functions 3 (VMF3) model (Landskron and Boehm 2017, DOI: 10.1007/s00190-017-1066-2).

    Hydrostatic and wet mapping function coefficients ($a_h$, $a_w$) and zenith delays (ZHD, ZWD) have to be provided via inputfileVmfCoefficients. This file can contain either station-specific data (see ViennaMappingFunctionStation2File) or data on a regular global grid (see ViennaMappingFunctionGrid2File). In the second case mapping coefficients and zenith delays are interpolated to the requested coordinates. This includes a height correction that requires approximate meteorological data provided via inputfileGpt.

    GPT

    Tropospheric delays based on the Global Pressure and Temperature 3 (GPT3) model (Landskron and Boehm 2017, DOI: 10.1007/s00190-017-1066-2).

    It is an empirical model derived from the Vienna Mapping Functions 3 (VMF3, see viennaMapping) and thus does not require additional mapping coefficients and zenith delay values.'}, +'troposphereType': { 'name': 'troposphereType', 'key': 'troposphereType', 'description': 'This class provides functions for calculating and estimating the signal delay in the dry and wet atmosphere. Tropospheric delays based on the Vienna Mapping Functions 3 (VMF3) model (Landskron and Boehm 2017, DOI: ). Hydrostatic and wet mapping function coefficients ( , ) and zenith delays (ZHD, ZWD) have to be provided via . This file can contain either station-specific data (see ViennaMappingFunctionStation2File ) or data on a regular global grid (see ViennaMappingFunctionGrid2File ). In the second case mapping coefficients and zenith delays are interpolated to the requested coordinates. This includes a height correction that requires approximate meteorological data provided via . Tropospheric delays based on the Global Pressure and Temperature 3 (GPT3) model (Landskron and Boehm 2017, DOI: ). It is an empirical model derived from the Vienna Mapping Functions 3 (VMF3, see ) and thus does not require additional mapping coefficients and zenith delay values. Tropospheric delays based on the Mendes-Pavlis model that employs meteorological data. (Mendes et al. (2002), DOI: and Mendes & Pavlis (2004), DOI: ) The meteorological data have to be provided via . This file contains the temperature, air pressure and humidity and must be first generated using the programs Crd2NormalPoints , Cstg2NormalPoints , Merit2NormalPoints or Merit2FullRate .', 'config_table': 'inputfileVmfCoefficients filename ah, aw, zhd, zwd coefficients inputfileGpt filename gridded GPT data aHeight double parameter a (height correction) bHeight double parameter b (height correction) cHeight double parameter c (height correction) inputfileGpt filename gridded GPT data aHeight double parameter a (height correction) bHeight double parameter b (height correction) cHeight double parameter c (height correction) inputfileStationMeteorology filename', 'display_text': 'This class provides functions for calculating and estimating the signal delay in the dry and wet atmosphere.

    ViennaMapping

    Tropospheric delays based on the Vienna Mapping Functions 3 (VMF3) model (Landskron and Boehm 2017, DOI: 10.1007/s00190-017-1066-2).

    Hydrostatic and wet mapping function coefficients ($a_h$, $a_w$) and zenith delays (ZHD, ZWD) have to be provided via inputfileVmfCoefficients. This file can contain either station-specific data (see ViennaMappingFunctionStation2File) or data on a regular global grid (see ViennaMappingFunctionGrid2File). In the second case mapping coefficients and zenith delays are interpolated to the requested coordinates. This includes a height correction that requires approximate meteorological data provided via inputfileGpt.

    GPT

    Tropospheric delays based on the Global Pressure and Temperature 3 (GPT3) model (Landskron and Boehm 2017, DOI: 10.1007/s00190-017-1066-2).

    It is an empirical model derived from the Vienna Mapping Functions 3 (VMF3, see viennaMapping) and thus does not require additional mapping coefficients and zenith delay values.

    MendesAndPavlis

    Tropospheric delays based on the Mendes-Pavlis model that employs meteorological data. (Mendes et al. (2002), DOI: 10.1029/2001GL014394 and Mendes & Pavlis (2004), DOI:110.1029/2004GL020308)

    The meteorological data have to be provided via inputfileStationMeteorology. This file contains the temperature, air pressure and humidity and must be first generated using the programs Crd2NormalPoints, Cstg2NormalPoints, Merit2NormalPoints or Merit2FullRate.'}, 'general.fileFormat': { 'name': 'general.fileFormat', 'key': 'general.fileFormat', 'description': 'All GROOPS files are written either in XML, binary, or ASCII format depending on the filename extension. .xml : XML format .dat : binary format .txt and all other extensions: ASCII format With an additional extension of \' .gz \' files are directly compressed and uncompressed. It is also possible to directly uncompress and read (but not write) \'d files (\' .Z \'). Comments are allowed in ASCII files and all the text starting from the character \' # \' to the end of the line is ignored. The program FileConvert can be used to convert between the different formats. This program is also useful to get some general information of files in binary format. The following special file types are used in GROOPS:', 'config_table': '', 'display_text': 'All GROOPS files are written either in XML, binary, or ASCII format depending on the filename extension.

    • .xml: XML format
    • .dat: binary format
    • .txt and all other extensions: ASCII format

    With an additional extension of \'.gz\' files are directly compressed and uncompressed. It is also possible to directly uncompress and read (but not write) Unix compress\'d files (\'.Z\').

    Comments are allowed in ASCII files and all the text starting from the character \'#\' to the end of the line is ignored.

    The program FileConvert can be used to convert between the different formats. This program is also useful to get some general information of files in binary format.

    The following special file types are used in GROOPS:'}, 'fileFormat_admittance': { 'name': 'Admittance', 'key': 'fileFormat_admittance', 'description': 'Interpolation matrix to create ocean minor tides from modeled major tides. The file can be created with DoodsonHarmonicsCalculateAdmittance and used e.g. in Interpolation matrix to create ocean minor tides from modeled major tides. The file can be created with . See DoodsonHarmonicsCalculateAdmittance .', 'config_table': '', 'display_text': 'Interpolation matrix to create ocean minor tides from modeled major tides. The file can be created with DoodsonHarmonicsCalculateAdmittance and used e.g. in doodsonHarmonicTide.

    See DoodsonHarmonicsCalculateAdmittance.'}, 'fileFormat_arcList': { 'name': 'ArcList', 'key': 'fileFormat_arcList', 'description': 'With the InstrumentSynchronize an instrument file can be divided into time intervals and within the intervals into arcs. This file provides the information about the mapping of arcs to time intervals. This file can be used for the variational equation approach or KalmanBuildNormals . groops arclist version=20200123 32 # number of times # time [MJD] first arc # ================================== 58909.000000000000000000 0 58910.000000000000000000 8 58911.000000000000000000 17 58912.000000000000000000 25 58913.000000000000000000 29 58914.000000000000000000 37 58915.000000000000000000 45 58916.000000000000000000 53 58917.000000000000000000 61 58918.000000000000000000 69 58919.000000000000000000 78 58920.000000000000000000 86 58921.000000000000000000 95 58922.000000000000000000 103 58923.000000000000000000 112 58924.000000000000000000 120 58925.000000000000000000 128 58926.000000000000000000 136 58927.000000000000000000 144 58928.000000000000000000 153 58929.000000000000000000 161 58930.000000000000000000 169 58931.000000000000000000 177 58932.000000000000000000 185 58933.000000000000000000 193 58934.000000000000000000 201 58935.000000000000000000 210 58936.000000000000000000 218 58937.000000000000000000 226 58938.000000000000000000 234 58939.000000000000000000 242 58940.000000000000000000 250', 'config_table': '', 'display_text': 'With the InstrumentSynchronize an instrument file can be divided into time intervals and within the intervals into arcs. This file provides the information about the mapping of arcs to time intervals.

    This file can be used for the variational equation approach or KalmanBuildNormals.

     groops arclist version=20200123          32  # number of times # time [MJD]               first arc # ==================================  58909.000000000000000000          0  58910.000000000000000000          8  58911.000000000000000000         17  58912.000000000000000000         25  58913.000000000000000000         29  58914.000000000000000000         37  58915.000000000000000000         45  58916.000000000000000000         53  58917.000000000000000000         61  58918.000000000000000000         69  58919.000000000000000000         78  58920.000000000000000000         86  58921.000000000000000000         95  58922.000000000000000000        103  58923.000000000000000000        112  58924.000000000000000000        120  58925.000000000000000000        128  58926.000000000000000000        136  58927.000000000000000000        144  58928.000000000000000000        153  58929.000000000000000000        161  58930.000000000000000000        169  58931.000000000000000000        177  58932.000000000000000000        185  58933.000000000000000000        193  58934.000000000000000000        201  58935.000000000000000000        210  58936.000000000000000000        218  58937.000000000000000000        226  58938.000000000000000000        234  58939.000000000000000000        242  58940.000000000000000000        250 
    '}, diff --git a/docs/html/instrumentTypeType.html b/docs/html/instrumentTypeType.html index d35e8f07..bf05a277 100644 --- a/docs/html/instrumentTypeType.html +++ b/docs/html/instrumentTypeType.html @@ -88,6 +88,8 @@

    InstrumentType

    GRADIOMETER
    xx, yy, zz, xy, xz, yz [1/s^2]
    GNSSRECEIVER
    GNSS phase/code observations [m]
    OBSERVATIONSIGMA
    accuracy +
    SATELLITELASERRANGING
    range [m], accuracy [m], redundancy, window [s], wavelength [m], azimuth [rad], elevation [rad] +
    METEOROLOGICAL
    temperature [K], pressure [Pa], humidity [%], windSpeed [m/s], radiation [W/m^2], precip. [mm/d]
    MASS
    THRUSTER
    MAGNETOMETER
    diff --git a/docs/html/platformSelectorType.html b/docs/html/platformSelectorType.html index 5a751b5d..a8bb8c91 100644 --- a/docs/html/platformSelectorType.html +++ b/docs/html/platformSelectorType.html @@ -74,7 +74,7 @@

    PlatformSelector

    Select a list of platforms (stations, satellites, ...). In a first step all platforms are selected if first selector excludes platforms otherwise all platforms excluded. When every selector from top to bottom selects or deselects -(with exclude) the matching platforms.

    See also GnssProcessing. +(with exclude) the matching platforms.

    See also GnssProcessing or SlrProcessing.

    All

    diff --git a/docs/html/programType.html b/docs/html/programType.html index aca1749a..58737199 100644 --- a/docs/html/programType.html +++ b/docs/html/programType.html @@ -318,6 +318,10 @@

    Simulation

  • SimulateStarCameraSentinel1
  • SimulateStarCameraTerrasar
  • +

    Slr

    +

    System

    • FileConvert
    • @@ -336,6 +340,9 @@

      Conversion

    • Champ2AccStar
    • Champ2Orbit
    • Cosmic2OrbitStar
    • +
    • Cpf2Orbit
    • +
    • Crd2NormalPoints
    • +
    • Cstg2NormalPoints
    • DoodsonAdmittance2SupplementaryFiles
    • DoodsonHarmonics2IersPotential
    • DoodsonHarmonics2IersWaterHeight
    • @@ -401,10 +408,13 @@

      Conversion

    • Igs2EarthOrientationParameter
    • Jason2Starcamera
    • JplAscii2Ephemerides
    • +
    • Merit2FullRate
    • +
    • Merit2NormalPoints
    • NetCdf2GriddedData
    • NetCdf2GriddedDataTimeSeries
    • NetCdfInfo
    • NormalsSphericalHarmonics2Sinex
    • +
    • Orbit2Cpf
    • Orbit2GroopsAscii
    • Orbit2Sp3Format
    • PotentialCoefficients2Icgem
    • @@ -416,8 +426,11 @@

      Conversion

    • Sinex2Normals
    • Sinex2StationDiscontinuities
    • Sinex2StationPositions
    • +
    • SinexEccentricties2SlrPlatform
    • SinexMetadata2GlonassFrequencyNumber
    • SinexMetadata2SatelliteModel
    • +
    • SlrComModel2RangeBiasStationSatellite
    • +
    • SlrSinexDataHandling2Files
    • Sp3Format2Orbit
    • Swarm2Starcamera
    • TerraSarTandem2Orbit
    • diff --git a/docs/html/slrParametrizationType.html b/docs/html/slrParametrizationType.html new file mode 100644 index 00000000..08817f79 --- /dev/null +++ b/docs/html/slrParametrizationType.html @@ -0,0 +1,382 @@ + + + + + GROOPS - slrParametrizationType + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
      + +
      +
      +
      + +

      SlrParametrization

      +This class defines the models and parameters of the linearized observation equations +for normal points (see SlrProcessing) +\[\label{slrParametrizationType:model} + \M l - \M f(\M x_0) = \left.\frac{\partial \M f(\M x)}{\partial \M x}\right|_{\M x_0} \Delta\M x + \M\epsilon, +\]where the left side is the observation vector minus the effects computed from the a priori models. +After each least squares adjustment +(see SlrProcessing:processingStep:estimate) +the a priori parameters are updated +\[\label{slrParametrizationType:update} + \M x_0 := \M x_0 + \Delta\hat{\M x}. +\]The vector $\M x_0$ can be written with +SlrProcessing:processingStep:writeAprioriSolution. +Any outputfiles defined in the parametrizations are written with +SlrProcessing:processingStep:writeResults.

      Each parametrization (and possible constraint equations) has a name which enables +activating/deactivating the estimation of subsets of $\Delta\M x$ with +SlrProcessing:processingStep:selectParametrizations. +The a priori model $\M f(\M x_0)$ is unaffected and is always reduced.

      The model for the one way range observations between station $s$ and reflector $r$ +can be described as +\[\label{slrParametrizationType:slrFullModel} +\begin{split} + f_s^r(\M x) &= \frac{1}{2}\left(\left\lVert \M r^r(t_{bounce})-\M r_s(t_{trans}) \right\rVert + + \left\lVert \M r_s(t_{recv})-\M r^r(t_{bounce}) \right\rVert\right) \\ + &+ \text{troposphere}(t,\M r_{ss}^r) + + \text{bias}^r + \text{bias}_s + \text{bias}_s^r + \text{other}(\ldots) + \epsilon_r^s +\end{split} +\] +See also SlrProcessing. +

      + +

      Troposphere

      +A priori tropospheric correction is handled by a troposphere model (e.g. Mendes and Pavlis). +Additional parameters in $[m]$ for zenith delay can be set up via +troposphereEstimation. +These parameters can be soft-constrained using +parametrization:constraints +to avoid an unsolvable system of normal equations in case of data gaps.

      The parameter names are <station>:troposphere:<temporal>:<interval>. +

      + + + + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      selectStations
      platformSelector
      outputfileTroposphere
      filenamecolumns: MJD, ZHD, ZWD, dry north gradient, wet north gradient, dry east gradient, wet east gradient
      troposphere
      tropospherea priori troposphere model
      troposphereEstimation
      parametrizationTemporal[m] parametrization of zenith delays
      + +

      DynamicOrbits

      +The estimation of (reduced) dynamic orbits is formulated as variational equations. +It is based on inputfileVariational calculated with PreprocessingVariationalEquation. +Necessary integrations are performed by integrating a moving interpolation polynomial of degree integrationDegree. +The parametrizationAcceleration must include at least those +parameters that were estimated in PreprocessingVariationalEquationOrbitFit. +Additional stochasticPulse parameters can be set up to reduce orbit mismodeling.

      The parameters and parameter names are divided into global +

        + +
      • <satellite>:<parametrizationAcceleration>:*:*, +
      • +<satellite>:stochasticPulse.x::<time>, +
      • +<satellite>:stochasticPulse.y::<time>, +
      • +<satellite>:stochasticPulse.z::<time>, +
      + +and arc related parameters +
        + +
      • <satellite>:arc<no>.<parametrizationAcceleration>:*:*, +
      • +<satellite>:arc<no>.position0.x::, +
      • +<satellite>:arc<no>.position0.y::, +
      • +<satellite>:arc<no>.position0.z::. +
      • +<satellite>:arc<no>.velocity0.x::, +
      • +<satellite>:arc<no>.velocity0.y::, +
      • +<satellite>:arc<no>.velocity0.z::. +
      + +

      + + + + + + + + + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      selectSatellites
      platformSelector
      outputfileOrbit
      filenamevariable {satellite} available
      outputfileParameters
      filenamevariable {satellite} available
      inputfileVariational
      filenamevariable {satellite} available
      stochasticPulse
      timeSeries[mu/s] parametrization of stochastic pulses
      parametrizationAcceleration
      parametrizationAccelerationorbit force parameters
      ephemerides
      ephemerides
      integrationDegree
      uintintegration of forces by polynomial approximation of degree n
      interpolationDegree
      uintfor orbit interpolation and velocity calculation
      + +

      GravityField

      +Estimates a (time depending) gravity field together with at least one +parametrization:dynamicOrbits. +The parametrization of the gravity field can be set with +parametrization.

      The parameter names are gravityfield:<parametrization>:*:*. +

      + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      parametrization
      parametrizationGravity
      + +

      StaticPositions

      +Estimates a static position for all +selectReceivers in the terrestrial frame.

      No-net constraints can be applied for a subset of stations, +selectNoNetReceivers, with a +standard deviation of noNetTranslationSigma and noNetRotationSigma and noNetScaleSigma and noNetScaleSigma. +If the template inputfileNoNetPositions is provided +the constraints are applied relatively to these positions. Only stations with an existing position file +are considered. Without inputfileNoNetPositions +the constraints are applied towards the apriori values from +SlrProcessing:station. +As a single corrupted station position can disturb the no-net conditions, +the rotation/translation parameters are estimated in a +robust least squares adjustment +beforehand. The computed weight matrix is used to downweight corrupted stations +in the constraint equations.

      In case you want to align to an ITRF/ILRS reference frame, precise coordinates can be +generated with Sinex2StationPositions.

      The parameter names are +

        + +
      • <station>:position.x::, +
      • +<station>:position.y::, +
      • +<station>:position.z::. +
      + +

      + + + + + + + + + + + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      selectStations
      platformSelector
      outputfileGriddedPosition
      filenamedelta north east up for all stations
      outputfilePosition
      filenamevariable {station} available, full estimated coordinates (in TRF)
      nameConstraint
      stringused for parameter selection
      selectNoNetStations
      platformSelector
      inputfileNoNetPositions
      filenamevariable {station} available, precise coordinates used for no-net constraints (in TRF)
      noNetTranslationSigma
      double(0 = unconstrained) sigma [m] for no-net translation constraint on station coordinates
      noNetRotationSigma
      double(0 = unconstrained) sigma [m] at Earth's surface for no-net rotation constraint on station coordinates
      noNetScaleSigma
      double(0 = unconstrained) sigma [m] for no-net scale constraint on station coordinates
      huber
      doublestations > huber*sigma0 are downweighted in no-net constraint
      huberPower
      doublestations > huber: sigma=(e/huber)^huberPower*sigma0
      + +

      EarthRotation

      +Earth rotation parameters (ERPs) can be estimated by defining +estimatePole ($x_p$, $y_p$) and estimateUT1 ($dUT1, LOD$).

      Estimating length of day (LOD) with the sign according to IGS conventions requires a negative +value in parametrizationTemporal:trend:timeStep.

      Constraints on the defined parameters can be added via +parametrization:constraints. +An example would be to set up estimateUT1:constant +so the $dUT1$ parameter is included in the normal equation system . Since $dUT1$ cannot be +determined by SLR, a hard constraint to its a priori value can then be added.

      The parameter names are +

        + +
      • earth:polarMotion.xp:<temporal>:<interval>, +
      • +earth:polarMotion.yp:<temporal>:<interval>, +
      • +earth:UT1:<temporal>:<interval>, +
      • +earth:nutation.X:<temporal>:<interval>, +
      • +earth:nutation.>:<temporal>:<interval>. +
      + +

      + + + + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      outputfileEOP
      filenameEOP time series (mjd, xp, yp, sp, dUT1, LOD, X, Y, S)
      estimatePole
      parametrizationTemporalxp, yp [mas]
      estimateUT1
      parametrizationTemporalrotation angle [ms]
      estimateNutation
      parametrizationTemporaldX, dY [mas]
      + +

      RangeBiasStationApriori

      +A priori station range bias value for all selectStations. +The ILRS provides the mean range biases ILRS Data Handling File, +but these have been determined using the passive satellites LAGEOS and Etalon and are therefore only suitable for passive +satellites and not for active ones. +Use SlrSinexDataHandling2Files to convert the range biases from +ILRS Data Handling File to instrument file. +

      + + + + +
      NameTypeAnnotation
      selectStations
      platformSelector
      inputfileRangeBias
      filenamevariable {station} available
      + +

      RangeBiasStation

      +Estimates a constant station range bias in $[m]$ for +selectStations.

      The parameter names are <station>:rangeBias::. +

      + + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      selectStations
      platformSelector
      outputfileRangeBias
      filenamevariable {station} available
      + +

      RangeBiasSatelliteApriori

      +A priori satellite range bias value for selectSatellites. +

      + + + + +
      NameTypeAnnotation
      selectSatellites
      platformSelector
      inputfileRangeBias
      filenamevariable {satellite} available
      + +

      RangeBiasSatellite

      +Estimates a constant satellite range bias in $[m]$ for +selectSatellites.

      The parameter names a <satellite>:rangeBias::. +

      + + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      selectSatellites
      platformSelector
      outputfileRangeBias
      filenamevariable {satellite} available
      + +

      RangeBiasStationSatelliteApriori

      +A priori station-satellite range bias value between all selectStations - +selectSatellites pairs.

      For standard ILRS processing this class should be setup twice. +Once for the model from José Rodríguez (see SlrComModel2RangeBiasStationSatellite) and additionally for +biases from the ILRS Data Handling File converted with SlrSinexDataHandling2Files. +

      + + + + + +
      NameTypeAnnotation
      selectStations
      platformSelector
      selectSatellites
      platformSelector
      inputfileRangeBias
      filenamevariable {station} and {satellite} available
      + +

      RangeBiasStationSatellite

      +Estimates the station-satellite range bias in $[m]$ between all +selectStations - +selectSatellites pairs.

      The parameter names are <station>.<satellite>:rangeBias::. +

      + + + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      selectStations
      platformSelector
      selectSatellites
      platformSelector
      outputfileRangeBias
      filenamevariable {station} and {satellite} available
      + +

      TimeBiasApriori

      +A priori time bias value for all selectStations. +The ILRS provides the mean time biases ILRS Data Handling File, +but these have been determined using the passive satellites LAGEOS and Etalon and are therefore only suitable for passive +satellites and not for active ones. +Use SlrSinexDataHandling2Files to convert the time biases from +ILRS Data Handling File to instrument file. +

      + + + + +
      NameTypeAnnotation
      selectStations
      platformSelector
      inputfileTimeBias
      filenamevariable {station} available
      + +

      TimeBias

      +Estimates a temporal changing +time bias in $[ms]$ for selectStations.

      The parameter names are <station>:timeBias:<temporal>:<interval>. +

      + + + + + +
      NameTypeAnnotation
      name
      stringused for parameter selection
      selectStations
      platformSelector
      estimateTimeBias
      parametrizationTemporal[ms]
      + +

      Constraints

      +Add a pseudo observation equation (constraint) +for each selected parameters +\[ + b-x_0 = 1 \cdot dx + \epsilon, +\]where $b$ is the bias and $x_0$ is the a priori value of the parameter +if relativeToApriori is not set. +The standard deviation sigma is used to weight the observation equations. +

      + + + + + + + +
      NameTypeAnnotation
      name
      string
      parameters
      parameterSelectorparameter to constrain
      sigma
      doublesigma of the constraint (same unit as parameter)
      bias
      doubleconstrain all selected parameters towards this value
      relativeToApriori
      booleanconstrain only dx and not full x=dx+x0
      + +

      Group

      +Groups a set of parameters. This class can be used to structure complex parametrizations +and has no further effect itself. +

      + + + +
      NameTypeAnnotation
      parametrization
      slrParametrization
      + +
      +
      + + diff --git a/docs/html/slrProcessingStepType.html b/docs/html/slrProcessingStepType.html new file mode 100644 index 00000000..d43caad4 --- /dev/null +++ b/docs/html/slrProcessingStepType.html @@ -0,0 +1,278 @@ + + + + + GROOPS - slrProcessingStepType + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
      + +
      +
      +
      + +

      SlrProcessingStep

      +Processing step in SlrProcessing.

      Processing steps enable a dynamic definition of the consecutive steps performed during any kind of SLR processing. +The most common steps are estimate, which performs an iterative least +squares adjustment, and writeResults, which writes all output files +defined in SlrProcessing and is usually the last step. +Some steps such as selectParametrizations +and selectStations affect all subsequent steps. +In case these steps are used within a group step, +they only affect the steps within this level. +

      + +

      Estimate

      +Iterative non-linear least squares adjustment. +In every iteration it accumulates the system of normal equations, solves the system and updates the estimated parameters. +The estimated parameters serve as a priori values in the next iteration and the following processing steps. +Iterates until either every single parameter update (converted to an influence in meter) +is below a convergenceThreshold or maxIterationCount is reached.

      With computeResiduals the observation equations are computed +again after each update to compute the observation residuals.

      The overall standard deviation of a single observation used for the weighting +is composed of several factors +\[ + \hat{\sigma}_i = \hat{\sigma}_i^{huber} \hat{\sigma}^{stat} \sigma_{apriori}^{stat}, +\]where the $\sigma_{apriori}^{stat}$ is given by station:accuracy. +The other factors are estimated iteratively from the residuals.

      With computeWeights a standardized variance $\hat{s}_i^2$ +for each residual $\hat{\epsilon}_i$ is computed +\[ + \hat{s}_i^2 = \frac{1}{\hat{\sigma}^{stat} \sigma_{apriori}^{stat}}\frac{\hat{\epsilon}_i^2}{r_i} + \qquad\text{with}\qquad + r_i = \left(\M A\left(\M A^T\M A\right)^{-1}\M A^T\right)_{ii} +\]taking the redundancy $r_i$ into account. If $\hat{s}_i$ is above a threshold huber +the observation gets a higher standard deviation used for weighting according to +\[ + \hat{\sigma}_i^{huber} = + \left\{ \begin{array}{ll} + 1 & s < huber,\\ + (\hat{s}_i/huber)^{huberPower} & s \ge huber + \end{array} \right., +\]similar to robust least squares adjustment.

      With adjustSigma0 an individual variance factor can be computed for each station separately +\[ + \hat{\sigma}^{stat} = \sqrt{\frac{\hat{\M\epsilon}^T\M P\hat{\M\epsilon}}{r}}. +\]

      + + + + + + + + + +
      NameTypeAnnotation
      computeResiduals
      boolean
      adjustSigma0
      booleanadjust sigma0 by scale factor (per station)
      computeWeights
      booleandownweight outliers
      huber
      doubleresiduals > huber*sigma0 are downweighted
      huberPower
      doubleresiduals > huber: sigma=(e/huber)^huberPower*sigma0
      convergenceThreshold
      double[m] stop iteration once full convergence is reached
      maxIterationCount
      uintmaximum number of iterations
      + +

      WriteResults

      +In this step all outputfiles defined in parametrizations +are written. It considers the settings of +processingStep:selectParametrizations +and processingStep:selectStations.

      It is usually the last processing step, but can also be used at other points in the +processing in combination with suffix to write intermediate results. +

      + + + +
      NameTypeAnnotation
      suffix
      stringappended to every output file name (e.g. orbit.G01.suffix.dat)
      + +

      WriteNormalEquations

      +Accumulates the normal equations matrix and writes it. +If remainingParameters +is set only the selected parameters are written to the normal equations +and all other parameters are eliminated beforehand (implicitly solved).

      The solution of the normals would results in $\Delta\M x$ +(see parametrizations). To write the +appropriate apriori vector $\M x_0$ use +processingStep:writeAprioriSolution. +

      + + + + + + +
      NameTypeAnnotation
      outputfileNormalEquations
      filenamenormals
      remainingParameters
      parameterSelectorparameter order/selection of output normal equations
      constraintsOnly
      booleanwrite only normals of constraints without observations
      defaultNormalsBlockSize
      uintblock size for distributing the normal equations, 0: one block, empty: original block size
      + +

      WriteAprioriSolution

      +Writes the current apriori vector $\M x_0$ +(see parametrizations). +If remainingParameters +is set only the selected parameters are written. +

      + + + + + +
      NameTypeAnnotation
      outputfileAprioriSolution
      filenamea priori parameters
      outputfileParameterNames
      filenameparameter names
      remainingParameters
      parameterSelectorparameter order/selection of output normal equations
      + +

      WriteResiduals

      +Writes the observation residuals for all +selectStations. For for each station-satellite +pair a file is written. The file name is interpreted as a template with +the variables {station} and {satellite} being replaced by the station name. +

      + + + + + +
      NameTypeAnnotation
      selectStations
      platformSelectorsubset of used stations
      selectSatellites
      platformSelectorsubset of used satellites
      outputfileResiduals
      filenamevariable {station} available
      + +

      WriteUsedStationList

      +Writes a list of stations (stations) which are used in the last step and +selected by selectStations. +

      + + + + +
      NameTypeAnnotation
      selectStations
      platformSelectorsubset of used stations
      outputfileUsedStationList
      filenameascii file with names of used stations
      + +

      WriteUsedSatelliteList

      +Writes a list of satellites which are used in the last step and +selected by selectSatellites. +

      + + + + +
      NameTypeAnnotation
      selectSatellites
      platformSelectorsubset of used satellites
      outputfileUsedSatelliteList
      filenameascii file with names
      + +

      PrintResidualStatistics

      +Print residual statistics. +

      +  station   sigma redundancy obsCount outlier
      +  ----------------------------------------------
      +  1874       0.52   0.86      22      1 (4.55 
      +  1889       1.20   0.98     186      5 (2.69 
      +  1890       0.63   0.77      14      1 (7.14 
      +  1891       0.49   0.50       6      0 (0.00 
      +  7237       1.08   0.95     236     14 (5.93 
      +  7394       0.36   0.88      26      0 (0.00 
      +  7811       0.38   0.41       5      0 (0.00 
      +  7819       1.21   0.94     120      1 (0.83 
      +  7821       0.69   0.95     202      3 (1.49 
      +  7827       0.40   0.85      29      1 (3.45 
      +  7839       0.52   0.93     143     10 (6.99 
      +  7840       0.15   0.80      16      0 (0.00 
      +  7841       0.26   0.90      56      1 (1.79 
      +  7941       0.55   0.92     277      5 (1.81 
      +  8834       0.66   0.88     101      1 (0.99 
      +  ----------------------------------------------
      +  satellite sigma redundancy obsCount outlier
      +  ----------------------------------------------
      +  lageos1    1.04   0.94     722     24 (3.32 
      +  lageos2    0.91   0.95     590     11 (1.86 
      +  etalon1    1.19   0.78      57      2 (3.51 
      +  etalon2    1.10   0.81      70      6 (8.57 
      +  ----------------------------------------------
      +
      +

      + +

      SelectParametrizations

      +Enable/disable parameter groups and constraint groups for subsequent steps, +e.g. processingStep:estimate or +processingStep:writeResults. +The name and nameConstraint of these groups +are defined in parametrizations. +Prior models or previously estimated parameters used as new apriori $\M x_0$ values are unaffected +and they are always reduced from the observations. This means all unselected parameters are kept fixed +to their last result. +

      + + + + + + + +
      NameTypeAnnotation
      parametrization
      choice
      enable
      sequence
      name
      stringwildcards: * and ?
      disable
      sequence
      name
      stringwildcards: * and ?
      + +

      SelectSatellites

      +This step can be used to process only a subset of satellites in subsequent processing steps. +

      + + + +
      NameTypeAnnotation
      selectSatellites
      platformSelector
      + +

      SelectStations

      +This step can be used to process only a subset of stations in subsequent processing steps. +

      + + + +
      NameTypeAnnotation
      selectStations
      platformSelector
      + +

      Group

      +Perform these processing steps. This step can be used to structure complex processing flows. +The select.. processing steps +defined within a group only affect the steps within this group. +

      + + + +
      NameTypeAnnotation
      processingStep
      slrProcessingStepsteps are processed consecutively
      + +
      +
      + + diff --git a/docs/html/slrSatelliteGeneratorType.html b/docs/html/slrSatelliteGeneratorType.html new file mode 100644 index 00000000..e127fcfe --- /dev/null +++ b/docs/html/slrSatelliteGeneratorType.html @@ -0,0 +1,99 @@ + + + + + GROOPS - slrSatelliteGeneratorType + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
      + +
      +
      +
      + +

      SlrSatelliteGenerator

      +Definition and basic information of SLR satellites.

      See also SlrProcessing. +

      + +

      Satellites

      +A list of satellite names must be provided via inputfileSatelliteList. +The other input files are read for each satellite, where the file name is interpreted as a template +with the variable {satellite} being replaced by the satellite name from list. +The inputfileSatelliteInfo contains information about laser retro-reflector, +optical reference point, retro-reflector orientation, range corrections and center of mass. +It can be created via PlatformCreate. +If inputfileAttitude ist not provided an orbit reference frame +(along, cross, nearly nadir) is assumed. +

      + + + + + + + +
      NameTypeAnnotation
      inputfileSatelliteList
      filenameascii file with satellite names, used to loop variable {satellite}
      inputfileSatelliteInfo
      filenamevariable {satellite} available
      inputfileOrbit
      filenamevariable {satellite} available
      inputfileAttitude
      filenamevariable {satellite} available
      interpolationDegree
      uintfor orbit interpolation and velocity calculation
      + +
      +
      + + diff --git a/docs/html/slrStationGeneratorType.html b/docs/html/slrStationGeneratorType.html new file mode 100644 index 00000000..323bde6d --- /dev/null +++ b/docs/html/slrStationGeneratorType.html @@ -0,0 +1,131 @@ + + + + + GROOPS - slrStationGeneratorType + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
      + +
      +
      +
      + +

      SlrStationGenerator

      +Definition and basic information of SLR ground stations.

      See also SlrProcessing. +

      + +

      Stations

      +A list of station names must be provided via inputfileStationList. +It defines the variable {station} for the station specific input files. +The inputfileStationInfo contains metadata information like station number, +station name and approximate station postion in terrestrial reference frame (TRF) +considering the station eccentricities. They can be created via SinexEccentricties2SlrPlatform +or PlatformCreate. The inputfileObservations are separate files +for each {station}-{satellite} pair. They can be converted from CRD +format via Crd2NormalPoints, CSTG format via Cstg2NormalPoints +and MERIT II format via Merit2NormalPoints and Merit2FullRate.

      The apriori observation weighting is defined by the expression accuracy in $[m]$. +The following variables are defined for each observation from the +inputfileObservations: {residual}, {accuracy}, +{redundancy}, {laserWavelength}, {azimut}, {elevation}. +Observations with non-positive accuracies are removed. +This can be used for a rough outlier removal by an expression such as +accuracy = if(abs(residual)>30, NAN, accuracy).

      The effects of loading and tidal deformation on station positions can be corrected for +via loadingDisplacement and +tidalDisplacement, respectively. +Tidal deformations typically include: +

        + +
      • earthTide: Earth tidal deformations (IERS conventions) +
      • +doodsonHarmonicTide: ocean tidal deformations + (e.g. fes2014b_n720, minDegree=1) +
      • +doodsonHarmonicTide: atmospheric tidal deformation + (e.g. AOD1B RL06, minDegree=1) +
      • +poleTide: pole tidal deformations (IERS conventions) +
      • +poleOceanTide: ocean pole tidal deformations (IERS conventions) +
      + +

      + + + + + + + + + + + + + + +
      NameTypeAnnotation
      inputfileStationList
      filenameascii file with station names
      inputfileStationInfo
      filenamestation metadata
      inputfileStationPosition
      filenamestation position
      inputfileObservations
      filenamevariable {station} {satellite} available
      accuracy
      expression[m] used for weighting, variables: {residual}, {accuracy}, {redundancy}, {laserWavelength}, {azimut}, {elevation}
      loadingDisplacement
      gravityfieldloading deformation
      tidalDisplacement
      tidestidal deformation
      ephemerides
      ephemeridesfor tidal deformation
      inputfileDeformationLoadLoveNumber
      filename
      inputfilePotentialLoadLoveNumber
      filenameif full potential is given and not only loading potential
      elevationCutOff
      angle[degree] ignore observations below cutoff
      interpolationDegree
      uintfor position interpolation
      + +
      +
      + + diff --git a/docs/html/troposphereType.html b/docs/html/troposphereType.html index 6d856590..5f9253c1 100644 --- a/docs/html/troposphereType.html +++ b/docs/html/troposphereType.html @@ -103,6 +103,17 @@

      GPT

      Tropospheric delays based on the Global Pressure

      aHeight
      doubleparameter a (height correction)
      bHeight
      doubleparameter b (height correction)
      cHeight
      doubleparameter c (height correction) + + +

      MendesAndPavlis

      Tropospheric delays based on the Mendes-Pavlis model that employs meteorological data. +(Mendes et al. (2002), DOI: 10.1029/2001GL014394 and +Mendes & Pavlis (2004), DOI:110.1029/2004GL020308)

      The meteorological data have to be provided via inputfileStationMeteorology. +This file contains the temperature, air pressure and humidity and must be first generated using the +programs Crd2NormalPoints, Cstg2NormalPoints, Merit2NormalPoints or Merit2FullRate. +

      + + +
      NameTypeAnnotation
      inputfileStationMeteorology
      filename
      diff --git a/docs/latex/classes.auto.tex b/docs/latex/classes.auto.tex index a8ac003f..cd7e5eed 100644 --- a/docs/latex/classes.auto.tex +++ b/docs/latex/classes.auto.tex @@ -3485,6 +3485,8 @@ \section{InstrumentType}\label{instrumentTypeType} \hfuzz=500pt\includegraphics[width=1em]{connector.pdf}\includegraphics[width=1em]{element-mustset.pdf}~GRADIOMETER & \hfuzz=500pt & \hfuzz=500pt xx, yy, zz, xy, xz, yz [1/s\textasciicircum{}2]\\ \hfuzz=500pt\includegraphics[width=1em]{connector.pdf}\includegraphics[width=1em]{element-mustset.pdf}~GNSSRECEIVER & \hfuzz=500pt & \hfuzz=500pt GNSS phase/code observations [m]\\ \hfuzz=500pt\includegraphics[width=1em]{connector.pdf}\includegraphics[width=1em]{element-mustset.pdf}~OBSERVATIONSIGMA & \hfuzz=500pt & \hfuzz=500pt accuracy\\ +\hfuzz=500pt\includegraphics[width=1em]{connector.pdf}\includegraphics[width=1em]{element-mustset.pdf}~SATELLITELASERRANGING & \hfuzz=500pt & \hfuzz=500pt range [m], accuracy [m], redundancy, window [s], wavelength [m], azimuth [rad], elevation [rad]\\ +\hfuzz=500pt\includegraphics[width=1em]{connector.pdf}\includegraphics[width=1em]{element-mustset.pdf}~METEOROLOGICAL & \hfuzz=500pt & \hfuzz=500pt temperature [K], pressure [Pa], humidity [\%], windSpeed [m/s], radiation [W/m\textasciicircum{}2], precip. [mm/d]\\ \hfuzz=500pt\includegraphics[width=1em]{connector.pdf}\includegraphics[width=1em]{element-mustset.pdf}~MASS & \hfuzz=500pt & \hfuzz=500pt \\ \hfuzz=500pt\includegraphics[width=1em]{connector.pdf}\includegraphics[width=1em]{element-mustset.pdf}~THRUSTER & \hfuzz=500pt & \hfuzz=500pt \\ \hfuzz=500pt\includegraphics[width=1em]{connector.pdf}\includegraphics[width=1em]{element-mustset.pdf}~MAGNETOMETER & \hfuzz=500pt & \hfuzz=500pt \\ @@ -6950,7 +6952,7 @@ \section{PlatformSelector}\label{platformSelectorType} otherwise all platforms excluded. When every selector from top to bottom selects or deselects (with \config{exclude}) the matching platforms. -See also \program{GnssProcessing}. +See also \program{GnssProcessing} or \program{SlrProcessing}. \subsection{All}\label{platformSelectorType:all} @@ -7966,12 +7968,52 @@ \section{SggRightSide}\label{sggRightSideType} \clearpage %================================== -\section{SphericalHarmonicsFilter}\label{sphericalHarmonicsFilterType} -Filtering of a spherical harmonics expansion. +\section{SlrParametrization}\label{slrParametrizationType} +This class defines the models and parameters of the linearized observation equations +for normal points (see \program{SlrProcessing}) +\begin{equation}\label{slrParametrizationType:model} + \M l - \M f(\M x_0) = \left.\frac{\partial \M f(\M x)}{\partial \M x}\right|_{\M x_0} \Delta\M x + \M\epsilon, +\end{equation} +where the left side is the observation vector minus the effects computed from the a priori models. +After each least squares adjustment +(see \configClass{SlrProcessing:processingStep:estimate}{slrProcessingStepType:estimate}) +the a priori parameters are updated +\begin{equation}\label{slrParametrizationType:update} + \M x_0 := \M x_0 + \Delta\hat{\M x}. +\end{equation} +The vector $\M x_0$ can be written with +\configClass{SlrProcessing:processingStep:writeAprioriSolution}{slrProcessingStepType:writeAprioriSolution}. +Any \config{outputfiles} defined in the parametrizations are written with +\configClass{SlrProcessing:processingStep:writeResults}{slrProcessingStepType:writeResults}. + +Each parametrization (and possible constraint equations) has a \config{name} which enables +activating/deactivating the estimation of subsets of $\Delta\M x$ with +\configClass{SlrProcessing:processingStep:selectParametrizations}{slrProcessingStepType:selectParametrizations}. +The a priori model $\M f(\M x_0)$ is unaffected and is always reduced. + +The model for the one way range observations between station $s$ and reflector $r$ +can be described as +\begin{equation}\label{slrParametrizationType:slrFullModel} +\begin{split} + f_s^r(\M x) &= \frac{1}{2}\left(\left\lVert \M r^r(t_{bounce})-\M r_s(t_{trans}) \right\rVert + + \left\lVert \M r_s(t_{recv})-\M r^r(t_{bounce}) \right\rVert\right) \\ + &+ \text{troposphere}(t,\M r_{ss}^r) + + \text{bias}^r + \text{bias}_s + \text{bias}_s^r + \text{other}(\ldots) + \epsilon_r^s +\end{split} +\end{equation} +See also \program{SlrProcessing}. -\subsection{DDK} -Orderwise filtering with the DDK filter by Kusche et al. 2009. + +\subsection{Troposphere}\label{slrParametrizationType:troposphere} +A priori tropospheric correction is handled by a \configClass{troposphere}{troposphereType} model (e.g. Mendes and Pavlis). +Additional parameters in $[m]$ for zenith delay can be set up via +\configClass{troposphereEstimation}{parametrizationTemporalType}. +These parameters can be soft-constrained using +\configClass{parametrization:constraints}{slrParametrizationType:constraints} +to avoid an unsolvable system of normal equations in case of data gaps. + +The \file{parameter names}{parameterName} are \verb|:troposphere::|. \keepXColumns @@ -7979,15 +8021,40 @@ \subsection{DDK} \hline Name & Type & Annotation\\ \hline -\hfuzz=500pt\includegraphics[width=1em]{element-mustset.pdf}~level & \hfuzz=500pt uint & \hfuzz=500pt DDK filter level (1, 2, 3, ..., 8)\\ -\hfuzz=500pt\includegraphics[width=1em]{element-mustset.pdf}~inputfileNormalEquation & \hfuzz=500pt filename & \hfuzz=500pt \\ +\hfuzz=500pt\includegraphics[width=1em]{element.pdf}~name & \hfuzz=500pt string & \hfuzz=500pt used for parameter selection\\ +\hfuzz=500pt\includegraphics[width=1em]{element-mustset-unbounded.pdf}~selectStations & \hfuzz=500pt \hyperref[platformSelectorType]{platformSelector} & \hfuzz=500pt \\ +\hfuzz=500pt\includegraphics[width=1em]{element.pdf}~outputfileTroposphere & \hfuzz=500pt filename & \hfuzz=500pt columns: MJD, ZHD, ZWD, dry north gradient, wet north gradient, dry east gradient, wet east gradient\\ +\hfuzz=500pt\includegraphics[width=1em]{element-mustset.pdf}~troposphere & \hfuzz=500pt \hyperref[troposphereType]{troposphere} & \hfuzz=500pt a priori troposphere model\\ +\hfuzz=500pt\includegraphics[width=1em]{element-unbounded.pdf}~troposphereEstimation & \hfuzz=500pt \hyperref[parametrizationTemporalType]{parametrizationTemporal} & \hfuzz=500pt [m] parametrization of zenith delays\\ \hline \end{tabularx} -\subsection{Gauss} -Filtering the spherical harmonics expansion with a Gaussian filter. -\config{radius} gives the filter radius on the Earth surface in km. +\subsection{DynamicOrbits}\label{slrParametrizationType:dynamicOrbits} +The estimation of (reduced) dynamic orbits is formulated as variational equations. +It is based on \configFile{inputfileVariational}{variationalEquation} calculated with \program{PreprocessingVariationalEquation}. +Necessary integrations are performed by integrating a moving interpolation polynomial of degree \config{integrationDegree}. +The \configClass{parametrizationAcceleration}{parametrizationAccelerationType} must include at least those +parameters that were estimated in \program{PreprocessingVariationalEquationOrbitFit}. +Additional \configClass{stochasticPulse}{timeSeriesType} parameters can be set up to reduce orbit mismodeling. + +The parameters and \file{parameter names}{parameterName} are divided into global +\begin{itemize} +\item \verb|::*:*|, +\item \verb|:stochasticPulse.x::

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