英文翻译运用于机场多普勒天气雷达的移动杂波频谱滤波器.docx
《英文翻译运用于机场多普勒天气雷达的移动杂波频谱滤波器.docx》由会员分享,可在线阅读,更多相关《英文翻译运用于机场多普勒天气雷达的移动杂波频谱滤波器.docx(19页珍藏版)》请在冰豆网上搜索。
![英文翻译运用于机场多普勒天气雷达的移动杂波频谱滤波器.docx](https://file1.bdocx.com/fileroot1/2023-1/29/052b8b39-fa7c-476a-a38a-7cd8ee72a2d8/052b8b39-fa7c-476a-a38a-7cd8ee72a2d81.gif)
英文翻译运用于机场多普勒天气雷达的移动杂波频谱滤波器
成都信息工程学院
毕业设计英文翻译
运用于机场多普勒天气雷达的移动杂波频谱滤波器
系别
电子工程学院
姓名
杨杰
专业
电子信息工程
班级
大气探测2班
学号
2007021206
MovingClutterSpectralFilterforTerminalDoppler
WeatherRadar
1.INTRODUCTION
Detectinglow-altitudewindshearinsupportofaviationsafetyandefficiencyistheprimarymissionoftheTerminalDopplerWeatherRadar(TDWR).Thewind-sheardetectionperformancedependsdirectlyonthequalityofthedataproducedbytheTDWR.Attimesthedataqualitysuffersfromthepresenceofclutter.Althoughstationarygroundcluttersignalscanberemovedbyahigh-passfilter,movingcluttersuchasbirdsandroadwaytrafficcannotbeattenuatedusingthesametechniquebecausetheirsignalpowercanexistanywhereintheDopplervelocityspectrum.Furthermore,becausetheTDWRisasingle-polarizationradar,polarimetrycannotbeusedtodiscriminatethesetypesofclutterfromatmosphericsignals.
ThemovingclutterproblemisexacerbatedatWesternsiteswithdrymicroburst,becausetheirlowsignal-to-noiseratios(SNRs)aremoreeasilymaskedbyunwantedmovingclutter.ForLasVegas(LAS),Nevada,theoffendingclutteristrafficonroadsthatareorientedalongtheradarlineofsightneartheairport.Theradarislocatedatasignificantlyhigheraltitudethanthetown,improvingthevisibilitytotheroads,andgivingLAStheworstroadclutterproblemofallTDWRsites.TheSaltLakeCity(SLC),Utah,airportislocatedneartheGreatSaltLake,whichisthebiggestinlandstagingareaformigratingseabirdsinthecountry.It,therefore,suffersfrombirdclutter,whichnotonlycanobscurewindshearsignaturesbutcanalsomimicthemtotriggerfalsealarms.TheTDWR“dry”siteissuesarediscussedinmoredetailbyCho(2008).
Inordertomitigatetheseproblems,wedevelopedamovingclutterspectralfilter(MCSF).Inthispaperwedescribethealgorithmandpresentpreliminarytestresults.
2.THEPROBLEM
Figure1illustratesoneofthedifficultieswithnotfilteringoutmovingcluttersignalsfromTDWRdata.Awidespreadcoherentbirdflighteventlikethishastwoofthecharacteristicsofamicroburst-outflowofheightenedreflectivityawayfromacentralsourceandvelocitydivergencealongtheradials.Thus,amicroburstdetectorisindangerofissuingafalsealertinthiscase.
Figure2showsDopplervelocityspectravs.rangeforamicroburstevent(left)andacasewithbirdsinmanydifferentrangegates(right).Notonlyaretherebirdsignaturesthatareisolatedinrange-Doppler,thereisafeatureinrangegates~40-50thatisquasi-continuousandlookssimilartoastrongwindshear.Thechallengeistofilterthebirdsignalsintheright-handcasebutnotthemicroburstintheleft-handcase.
Figure1ExampleofbirdclutterobservedwiththeSLCTDWRat0.5°elevation.
Leftpanelshowsreflectivity,rightpanelshowsradialvelocity.
Figure2.Dopplervelocityspectravs.rangeforamicroburstcaseobservedwiththeProgramSupportFacility(PSF)TDWRinOklahomaCity,OKat0.3°elevation(left),andawidespreadbirdcontaminationcaseobservedwiththeSLCTDWRat0.5elevation(right).
Batscanalsocausesimilarproblemsforradarwindsheardetectionwhentheyleavetheirroostsenmasseatdusk.
Roadandrailtrafficarealsosourcesofmovingclutter.Inthiscase,therange-azimuthcellsaffectedareknownapriori,sothecurrentmethodofdealingwiththeproblemistoperiodicallygenerateaclutterresiduemap(CREM)andthencensorthebasedatawherethereflectivitydoesnotexceedacertainamountovertheCREMreflectivity.TheLASroadclutterproblemisshowninFigure3.Notethatsomeoftheclearestroadechoeslineupwiththeradarline-of-sightradials.Thisphenomenonisalsoobservedatothersites,andwecallitthebuildingcanyoneffect.Inanurbanenvironmentroadsarelinedwithbuildings,sotrafficisoftennotvisibletotheradarunlessthebeamshootsdownalongtheroaditself.
Figure3.LASroadclutterat0.8°elevation.Leftpanelshowsreflectivity,rightpanelshowsradialvelocity.Thelargewedgeofblankreflectivitytothenortheastoftheradarisduetoterrainblockage.
Airplanes,ofcourse,arealsomovingclutter.Becausetheyareisolatedtargets,apointtargetfilterdealswiththemeffectively.Althoughthecurrentoperationalalgorithmmerelycensorsthesepoints,weplantointerpolatethebasedataacrossthesepointsinthenextmajorradardataacquisition(RDA)systemsoftwarerevision.Thefilteringalgorithmpresentedinthispapershouldbeanevenbettersolutioninthefuture.
Finally,thereareothermovingtargetsthatappearinTDWRdatasuchasseaclutterandthespinningbladesofawindpowerturbine.Thelatterisexpectedtobeanever-growingsourceofclutterthatisstillinsearchofasolution.Theworkpresentedinthispaperdoesnotspecificallyaddressthesephenomena,asthefocushasbeenonthedataqualityissuesatSLCandLAS.
3.MOVINGCLUTTERSPECTRALFILTER
Stationaryclutterfiltersaretypicallyappliedononerange-azimuthdwelldataatatime.Recognizingthatmorecontextualinformationisnecessarytoidentifymovingclutter,techniquesweredevelopedthatutilizemultiplerangegatesofdata.ThepointtargetfiltersemployedonboththeTDWRandtheWeatherSurveil-lanceRadar-1988Doppler(WSR-88D,morecommonlyknownasNEXRAD)lookfortargetswithreflectivitymuchhigherthantheneighboringrangegates.Thistypeoffiltercanremoveaircraftandisolatedaviansignals,buttheweatherreturnsinthesamecellsarealsolost.
Amoremodernapproachfiltersdatainthetwo-dimensional(2D),Dopplervelocityspectrumvs.range,domain(e.g.,Sasaoka2003;Meymaris2007).Becausemovingclutterspectralsignalstendtobespectrallycompactanddiscontinuousinrange,thesetechniqueswouldlookforarange-continuoussignal(weather)anddiscardotherspectralcomponents(clutter).(Ofcourse,stationarygroundcluttercanalsobecontinuousinrange,soitwouldhavetobefilteredoutfirst.)Twodrawbackstothisapproacharethatitiscomputationallyintensiverelativetotraditionalweatherradarsignalprocessing,andthattheoutputbasedataaresmoothedinrange.
WiththedevelopmentofanewRDAsystem(Choetal.2005),whichiscurrentlyrunningoperationallyatLASandSLC,thereisconsiderablesparecomputationalcapacityfortheimplementationoffuturealgorithms.Thescalablearchitectureeasilyallowsforadditional(and/orupgraded)centralprocessingunits(CPUs)tobeinstalledtomeetfurthercomputationaldemand.Withregardtotheseconddrawbackoftheexisting2Dspectralprocessingapproachformovingclutterfiltering,spatialsmoothingofthedatarunscountertotheTDWR’smissionofdetectingwindshear.ThisisthereasonwhywedecidedtodevelopourownmovingclutterspectralfilterfortheTDWR.
First,wewillgiveabriefoutlineoftheMCSFalgorithm,andthendelveintomoredetails.
Tosetuptheprocessingenvironment,weformaDopplervelocitypowerspectrumateachrangegatewiththeusualwindow-and-DFTapproach.Thesespectraarestoredina2Dmatrix(Figure2,right).Thefollowingstepsarethenfollowed.
1)Removestationarygroundclutterwiththespectralfilterofchoice(Figure5).
2)Removepositivepoweranomaliesalongrangeateachspectralbininamannersimilartoapointtargetfilter(Figure6).Cluttersignalsthatarenotcontinuousinrangeareremovedinthisway.
3)Aftersuitabledatamassaging,determinethenumberandlocationofspectralmodes(statisticallysignificantpeaks)ateachrangegate.Ameasurecalledthenormalizedcircularexcessmass(NCEM)isusedtowinnowout"insignificant"peaksinthespectra.
4)Selectonemodeateachrangegatesuchthatthepathconnectingthemodeshastheshortestpossibleoveralldistance(Figure7).Thisprocessfavorsretaininggloballycontinuous(inrange)signalsoveronlylocallycontinuousfeatures.Theassumptionisthatatmosphericsignalswillbecontinuousoverlongerrangesthanmovingclutterfeatures.
Figure5.StationarygroundclutterisremovedFigure6.Isolatedspectralpeaksareremoved
fromthespectrashowninFigure2,right.fromthespectrashowninFigure5.
5)Formodesotherthantheonesselectedbytheshortestconnectingpath,reducethenumberof"extra"modesusingastricterNCEMthreshold.Thisstepisneededtoreducetheincidenceofthese"extra"modesbeingpartoftheatmosphericspectrum.
6)Anyleftover"extra"modesaredeemedtobemovingclutterandareremovedbyfillinginwiththecomputedspectral"noise"floor(Figure8).
7)Carryonwiththerestoftheusualsignalprocessingforbasedatageneration.
Letusnowelaborateoneachstep.(Note:
Theterm"circular"usedinthispaperreferstothefactthattheDopplervelocityspectrumaliases,orwrapsaround,attheendpoints.)Thereisnothingspecialaboutthefirststepofstationaryclutterfiltering.Oneofvariousdifferenttechniquescanbeused.However,notethattheGaussianmodeladaptiveprocessing(GMAP)filter(SiggiaandPassarelli2004)assumestheabsenceofspectralsignalotherthanastationarygroundclutterpeakandaGaussianweathercomponent.Therefore,thepresenceofmovingcluttersignalsdistortstheweathermomentestimationandcanspuriouslywidenthe"weather"spectrumwithinthefilledgroundcluttergap.We,thus,recommendagainsttheuseofGaussianfittingandclutter-gapfillinginthesuspectedpresenceofmovingclutter.
Theisolatedspectralpeakfilterinstep2issimilartotheTDWRpointtargetfilter,exceptthatitrunsalongeachspectralbinvs.range,andthenumberofneighborsconsidered