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1、HindawiPublishingCorporationInternationalJournalofDistributedSensorNetworksVolume2012,ArticleID592471,15pagesdoi:10.1155/2012/592471ResearchArticleAdaptiveSourceLocationEstimationBasedonCompressedSensinginWirelessSensorNetworksLeiLiu,1,2Jin-SongChong,1Xiao-QingWang,1andWenHong11NationalKeyLaborator
2、yofScienceandTechnologyonMicrowaveImaging,InstituteofElectronics,ChineseAcademyofSciences,Beijing100190,China2GraduateUniversityofChineseAcademyofSciences,Beijing100049,ChinaCorrespondenceshouldbeaddressedtoLeiLiu,liulei2111@gmail.comReceived19March2011;Revised3July2011;Accepted14September2011Acade
3、micEditor:RajgopalKannanCopyright©2012LeiLiuetal.ThisisanopenaccessarticledistributedundertheCreativeCommonsAttributionLicense,whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkisproperlycited.Sourcelocalizationisanimportantprobleminwirelesssensornetworks(WS
4、Ns).Anexcitingstate-of-the-artalgorithmforthisproblemismaximumlikelihood(ML),whichhassufficientspatialsamplesandconsumesmuchenergy.Inthispaper,aneffectivemethodbasedoncompressedsensing(CS)isproposedformultiplesourcelocationsinreceivedsignalstrength-wirelesssensornetworks(RSS-WSNs).Thisalgorithmmodelsu
5、nknownmultiplesourcepositionsasasparsevectorbyconstructingredundantdictionaries.Thus,sourceparameters,suchassourcepositionsandenergy,canbeestimatedby1-normminimization.Tospeedupthealgorithm,aneffectiveconstructionofmultiresolutiondictionaryisintroduced.Furthermore,toimprovethecapacityofresolvingtwo
6、sourcesthatareclosetoeachother,theadaptivedictionaryrefinementandtheoptimizationoftheredundantdictionaryarrangement(RDA)areutilized.ComparedtoMLmethods,suchasalternatingprojection,theCSalgorithmcanimprovetheresolutionofmultiplesourcesandreducespatialsamplesofWSNs.Thesimulationsresultsdemonstratethep
7、erformanceofthisalgorithm.1.IntroductionDOAandTDOAarenotverypracticalforlow-costandlow-powerWSNs.RSScaneffectivelyovercomethelimitationsWirelesssensornetworks(WSNs)[1,2]arewidelyappliedinofDOAandTDOA,thusinc
