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WAS-GMTI模式下基于Relax算法的杂波抑制和参数估计方法.docx

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WAS-GMTI模式下基于Relax算法的杂波抑制和参数估计方法 Abstract: Inthispaper,acluttersuppressionandparameterestimationmethodbasedontheRelaxalgorithmintheWAS-GMTImodeisproposed.Themethodcaneffectivelysuppressgroundclutterandestimatethemovingtargetparametersundercomplexinterferenceconditions.Theexperimentalresultsshowthattheproposedmethodhasbetterperformancethanthetraditionalmethodsintermsofcluttersuppressionandtargetparameterestimationaccuracy. Introduction: Withthedevelopmentofradartechnology,themovingtargetdetectionhasattractedmoreandmoreattention.TheGroundMovingTargetIndicator(GMTI)modeiswidelyusedinmodernradarsystemstodetectmovingtargets.However,duetothescatteringeffectsofvariousobstaclesontheground,theradarsignalreceivedbythereceiverisoftenaccompaniedbyalargeamountofclutter,whichseriouslyaffectsthedetectionandtrackingofmovingtargets. Cluttersuppressionisanimportantresearchdirectioninradarsignalprocessing.Variouscluttersuppressionmethodshavebeenproposedinthepastfewdecades,suchastheConstantFalseAlarmRate(CFAR)algorithm,MaximumLikelihood(ML)algorithm,andthePrincipalComponentAnalysis(PCA)basedalgorithm.However,thesemethodshaveshortcomingsincomplexinterferenceconditionsandneedtobeoptimized. TheRelaxalgorithmproposedinthispaperistosolvetheproblemsofcluttersuppressionandparameterestimationintheWAS-GMTImodeundercomplexinterferenceconditions. Theory: TheRelaxalgorithmisasignalprocessingmethodbasedontheL-infinityproblem.Thebasicideaistoiterativelysolvethefollowingoptimizationproblem: minimize||Wx||_inf,subjecttoAx=b wherexistheunknownsignal,Aisthemeasurementmatrix,bisthemeasurementvector,andWisadiagonalweightingmatrix.Thesolutionoftheaboveproblemcanbeobtainedbyiterativelysolvingthefollowingsub-problems: xi=argmin||Wx||_inf,subjecttoAix=bi Theabovesub-problemshaveaclosed-formsolution,whichcanbesolvedefficientlybylinearprogramming.TheRelaxalgorithmhastheadvantagesofsimpleimplementation,fastconvergence,andgoodperformance. Proposedmethod: IntheWAS-GMTImode,thereceivedsignalconsistsofclutterandmovi