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InSARMethodsandApplicationsHowardZebkerStanfordUniversityWhatisaradar?•Radar:RadioDetectionandRanging•MeasurestimeofflightofEMpulsesEarlyradarsTaylorandYoung(1922)BreitandTuve(1925)DistancemeasurementsMappingmultipleobjects-ppiImaginggeometryForminganimageRadarblockdiagramImagingradarblockdiagramRadarequationAntennagainG4A2•Antennadirectsenergyinonedirection•“Gain”definedasratioofilluminatedconetototalsolidangleLHLHIlluminatedarea2H•LSpherearea4Radarcrosssection•Radarequationrequirescrosssection•Distributedtargets:normalizedcrosssection(0)multipliedbypulse-limitedarea–Rangeillumination:–Azimuthillumination:sin2crLRazsinL2Rc0SignaltonoiseratioAbsolutelevelofpowernotreallyrelevantWhatcountsishowmuchlargersignalisthannoiseSignaltonoiseratio(SNR)=Psig/PnoiseThedBtablePropertiesofanEMwave•Observablesarefrequency,amplitude,phase,anddirection•PhasornotationdropsexplicittimedependenceE(t,r)=Acos[2ft-2r+]Eeje2rPhaseofanEMwaveDistancetraveledismeasuredasphaseofwaveObservedphaseofaradarechoobservedscatterer4rRanger-(two-waytravel)InSARgeometryandphaseAntenna1Antenna2r1r2PhasecalculationE2ejscattererej4r2E1ejscattererej4r1E1E2*ej4(r1r2)or,simply,4(r1r2)InSARgeometryrr+rrInSARphase-topographyr4sin()(rr)2r2B22rBz(y)hrcosInSARgeometry-deformationrr+rrrInSARdeformationphase•Phasesimilartobeforebutnowhasdisplacementterm•Toinferdeformation,getdifferenceandcompensatefortopoterm,leavingonlydeformationsignal2(def)24rPhasenoisensignal1SNRDecorrelation•Baselinedecorrelation•Temporaldecorrelation•Rotationaldecorrelation•Unspecifiednoisesinsystem–Thermaleffects–Quantization–OthernonlinearitiesDecorrelationsourcesQuantifyingdecorrelations1s2*s1s1*s2s2*Measuredas:Modeledas:s1=c+n1s2=c+n2then=c2c2n211SNR1SignalModels1f(xx0,yy0)exp{j4(rysin1)}W(x,y)dxdyn1ysinyPBaselinedecorrelationCalculatecross-correlations1s2*andsincethecorrelationisproportionaltos1s2*f(xx0,yy0)f*(x'x0,y'y0)exp{j4y(sin1sin2)}W(x,y)W*(x',y')dxdydx'dy'f(xx0,yy0)f*(x'x0,y'y0)0xx',yy's1s2*exp{j4ycos}W(x,y)2dxdyBaselinedecorrelationplotTheoreticalObserved10CorrelationBaseline,m050002500Seasatsatellite-L-bandRotational,temporaldecorrelationRMSscatterermotion,cm01020Rotation,deg01210CorrelationL-bandC-bandTemporaldecorrelationdata-L-bandDeathValleyfloorOregonlavaflowsOregonforestCorrelationTime,days0101020Massbalance*********AccumulationMeltingAblationSnowfallOutletGlaciersBedrockFlowEquilibriumLinePhysicalprocessesdrivingmassbalanceVolumescatteringmodelsGrainboundarymigrationScatteringdominatedby0.1mmgrainsScatteringdominatedby0.5mmgrainsDiffusionfromsmallgrainstolargergrainsFreshly-fallensnowOlder,buriedsnowAccumulationinlayeredmediaLayeredmodelAccumulationrateInferredlayerspacingInSARlimitedbydecorrelation•Arealcoveragelimitedtoareaswithhighcorrelation,oftenfailsinvegetatedregionsCorrelation(orange=high)PhaseLongValleycalderaPersistentscattererprincipleDistributedscattererSinglepointscattererDominantscattererPixelphaseAcquisition2AmplitudedispersionproxyforphasenoiseSpeckleobservedasimageamplitudevariationEarlyPSworkedwellinurbanareasSanFranciscoBayAreaFromFerrettietal.,EOS,2004ProblemsusingamplitudedispersionPS?ObservedphaseissumofmanycomponentsinsardeftopoatmorbitnoiseCorrelatedwithbaselineCorrelatedlocally-spatiallyUncorrelatedintimeCorrelatedglobally-spatiallyPSpixelshavelownoiseTopoerrortermcorrelatedwithbaselineEstimatetopoerrorandsubtractfromeachobservationTopoerrorproportionaltoredlineslopeFiltertoextractspatiallycorrelatedsignalFiltercalculatesvariancewithincirclePixelsthatpassfilterareretainedwithphasesLongValley-interferogramsandPSSept.1992Aug.2000InterferogramsPSnetworksInterferogramvs.PS“Good”qualitydata“Poor”qualitydataInterferogramPSnetworkLongValleyunwrapped
本文标题:InSAR技术入门-zebker
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