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1、DIGITALSIGNALPROCESSING8,185±210(1998)ARTICLENO.SP980316CovarianceMatchingEstimationTechniquesforArraySignalProcessingApplicationsB.Ottersten,*,²P.Stoica,³andR.Roy§*SignalProcessing/S3,RoyalInstituteofTechnology,SE-10044Stockholm,Sweden;³SystemsandControl,UppsalaUniversity,Box27,SE-75103Uppsala,
2、Sweden;and§ArrayComm,Inc.,3141ZankerRoad,SanJose,California951341.INTRODUCTIONOttersten,B.,Stoica,P.,andRoy,R.,CovarianceMatch-ingEstimationTechniquesforArraySignalProcessingApplications,DigitalSignalProcessing8(1998),185±210.Signalparameterestimationfromsensorarraydataisaproblemthatfrequentlyar
3、isesinmanyAclassofcovariancematchingestimationtechniquesapplications.Examplesincludetargetlocalization(COMET)hasrecentlyattractedinterestinthesignalprocess-withphasedarrayradars,detectionandclassi®ca-ingcommunity.Thesetechniqueshavetheirrootsinthetionofsourceswithunderwaterarrays,and,morestatist
4、icalliteraturewheretheyaresometimesreferredtorecently,interferencerejectionandsignalseparationasgeneralizedleastsquaresmethods.Covariancematch-inwirelesscommunicationsusingantennaarrays.Aingisanalternativetomaximumlikelihoodestimation,providingthesamelargesamplepropertiesoftenatalargeclassofesti
5、mationanddetectionmethodshaslowercomputationalcost.Herein,wepresentageneralbeendeveloped;mostofthesemethodsarebasedonframeworkforcovariancematchingtechniquesandshowamodelofthesensorarrayresponse.Thismodelisthattheyarewellsuitedtosolveseveralproblemsarisingeitherderivedanalyticallyorobtainedfromc
6、alibra-inarraysignalprocessing.Astraightforwardderivationoftionmeasurements.Thus,thesensorarrayreceivertheCOMETcriterionfrom®rstprinciplesispresented,outputsareassumedtobeaknownfunctionofthewhichalsoestablishesthelargesamplepropertiesofthesignalparameterswhichmayincludeazimuth,eleva-estimator.Cl
7、osedformcompactexpressionsfortheasymp-tion,polarization,etc.toticcovarianceoftheestimatesoftheparametersofAlargenumberofalgorithmshavebeendevisedinterestarealsoderived.Somedetectionschemesarere-forthesensorarrayproblem.Theso
