Processing large volume GPS data via Bernese V4.2 software · 2009. 11. 13. · Processing large...

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Processing large volume GPS data via Bernese V4.2 software C. MITSAKAKI, A. MARINOU, X. PAPANIKOLAOU, K. PAPAZISSI

Transcript of Processing large volume GPS data via Bernese V4.2 software · 2009. 11. 13. · Processing large...

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Processing large volume GPS data via Bernese V4.2 software

C.MITSAKAKI,A.MARINOU,X.PAPANIKOLAOU,K.PAPAZISSI

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SLRTrackingofGNSSConstellations50YearsofSatelliteGeodesyandGeodynamics

September14‐19,2009,Metsovo,

Greece

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Introduction

•  Deformation monitoring studies combine large amount of GNSS data and offer high quality products (coordinates/velocities).

•  Data analysis is performed via software packages applying statistical models (Least Squares/Kalman filter etc).

•  Users and software products have to address the growing demands for accuracy, high resolution, observation volume, reliability estimates.

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Dataanalysis

•  Higher Geodesy Laboratory and Dionysos Satellite Observatory of NTUA have participated in a European inter-disciplinary research programme by establishing and maintaining a network throughout Central Greece, to study the long term tectonic behaviour.

•  Two GPS campaigns are analyzed and discussed: 1.  Epoch 1997.76 (11 days of observations -150 network points) 2.  Epoch 2005.76 (10 days of observations - 71 network points)

•  Both networks were tied to the ITRF2000 via 7 IGS stations

•  The results of the 30 first order network common points are discussed here.

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Figure1

Epoch1997.761stordernetwork Epoch2005.761stordernetwork

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Figure2 IGSstationsusedforreferringtotheITRF2000

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•  DataanalyzedbyBERNESEV4.2GPSsoftware

•  PreciseIGSorbitsandcorrespondingpole•  IGSphaseeccentricityfile

•  Baselineapproachwasused•  AmbiguitiesresolvedusingtheQ.I.F(QuasiIonosphereFree)

methodwithrejectionlimitof85%.

•  Ionospheremodelusedforbaselineslongerthan400km•  Dailynormalequationsevaluatedfortheadjustment/

estimationprocedures.

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SolutionA dailycoordinateestimationsasanon‐weighted averageusingonlysub‐programmeGPEST

SolutionB Combinedadjustmentofdailynormalequations, usingparametereliminationfortroposphere

parameters(viasub‐programmeADDNEQ) Parametereliminationisanalgorithmtoreducethevolumeofparameters,whilenoa‐

prioriinformationislost.TroposphereparametersoccupythebiggestpartofNEQfiles.

SolutionC Combinedadjustmentofdailycoordinatesusing correspondingdailyVarCovarmatrices(via

sub‐programmeCOMPAR)

A‐prioriinformationaretheresultsfromsub‐programmeGPEST(SolutionA)

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Finalestimateswerecalculatedbythree different methods:

SolutionA

SolutionBand

SolutionC

Figure3

A

B

C

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ComparisonoftheSolutions

Figure4

•  Coordinatediscrepanciesvaryupto6mmforthehorizontalandupto18mmfortheheightcomponents

•  Discrepanciesareinmostcaseswithinobservationnoise

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Figure4(cont.)•  Coordinatediscrepanciesvaryupto6mmforthehorizontalandupto

20mmfortheheightcomponents

•  Discrepanciesareinmostcaseswithinobservationnoise

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Epoch 1997.76 Epoch 2005.76

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•  SolutionsBandCprovidepracticallyidenticalresults

Figure4(cont.)

Table1

•  Coordinatediscrepanciesvaryupto6mmforthehorizontalandupto18mmfortheheightcomponents

•  Discrepanciesareinmostcaseswithinobservationnoise 12

discrepancies between solutions

Epoch 1997.76 Epoch 2005.76

!N (mm) !E (mm) !U (mm) !N (mm) !E (mm) !U (mm)

mean 0.1 -0.1 0.4 0.2 -0.5 0.6 max 1.8 5.7 13.5 2.5 2.9 17.9

Epoch 2005.76 Epoch 1997.76

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ErrorAnalysis•  Eachestimateisaccompaniedbyanaposterioristandarderrorvalueforall

solutions.ApartfromsolutionA,qualityestimatesareunrealistic(largevolumeofdataexcessivedegreesoffreedom).

•  DespitethesmalldiscrepanciesincoordinateestimatesbetweentheSolutionsBandCthecorrespondingaposterioristandarderrorvaluesarenotthesame.

13Figure 5

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•  Aftereachdayisprocessedtwoslightlydifferentaposterioristandarderrorvalues(inourcase<0.8mm)maybecomputed:

Oneiscomputedfromthesub‐programmeGPESTtobeusedbythe sub‐programmeCOMPAR(SolutionC).

Thesecondonefromthesub‐programmeADDNEQ(SolutionB)

•  Thereforetheapriorivarianceofthecombinedsolutions(BorC)maybecalculatedfrom:

where:

:theapriorivarianceofunitweightofthecombinedsolution,

:thedegreesoffreedomfordayi,

:thevarianceofunitweightcomputedfromdayi

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•  Table 2      Aprioriandaposterioristandarderrorsofunitweightforthecombinedsolution(BandC)andforbothepochsofGPSobservations

aprioristandarderrorofunitweightcomputedfromdayifromthesub‐programme ADDNEQ

aprioristandarderrorofunitweightcomputedfromdayifromthesub‐programme GPEST

aposterioristandarderrorofunitweightofthecombinedsolution aposterioristandarderrorofunitweightofthecoordinategroupcomputedfromADDNEQ

(SolutionB)

aposterioristandarderrorofunitweightforcoordinatecomparisoncomputedfrom COMPAR(SolutionC)

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Solution B Solution C Epoch

a-priori (mm)

1.2 1.7 1997.76

1.4 2.0 2005.76

a-posteriori (mm) 1.3 20.1 1.2 13.1 1997.76

1.5 25.4 1.5 23.9 2005.76

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•  AposterioristandarderrorvaluesforsolutionCseemtobeinclose(linear)relationwithstandarderrorsfromsolutionA

•  Alinearmodelwasappliedtothetwoepochsdatasets.Residualsdispersesignificantlyforstandarderrorvalues>20mm.

•  Discardingsuchpointsandre‐applyingthelinearmodel,resultedinalmostidenticalparameters(forallcomponentsandbothepochs).

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Figure 6

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•  Table3   Parametersofthelinearmodelforeachcoordinatecomponentandbothepochs

•  Sofarnoreliableconclusionsmaybereached.

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Component X Y Z a b a b a b

Epoch 1997.76 0.36 0.7 0.39 0.2 0.37 0.7

Epoch 2005.76 0.42 -0.2 0.34 0.3 0.44 -0.3

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•  SolutionAprovidesrealisticstandarderrorvalues

•  SolutionBprovidesreliablecoordinateestimates

•  Offersawidevarietyofoptions•  Canprocessallkindof

parameters

•  SolutionCoffersreliablecoordinateestimates

•  Easytouse•  Standarderrorvaluesseemtobe

incloserelationwiththevaluesfromSolutionA

•  Itisrathertime‐consuming(notfullyautomated)

•  Canbeheavilyinfluencedbyerrorssinceitconsidersequallyweightedestimates

•  Notrealisticstandarderrorvalues•  Rathertimeconsuming

(parameterelimination)

•  Canonlybeusedforcoordinateestimation(geodeticapplications)

•  Cannotchangetheinitialminimumsetofconstraintschosenforthesolution

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