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    Adaptive Source Location Estimation Based on Compressed Sensing in Wireless Sensor Networks

    Adaptive Source Location Estimation Based on Compressed Sensing in Wireless Sensor Networks

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    時(shí)間:2019-08-04

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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),whichhassu?cientspatialsamplesandconsumesmuchenergy.Inthispaper,ane?ectivemethodbasedoncompressedsensing(CS)isproposedformultiplesourcelocationsinreceivedsignalstrength-wirelesssensornetworks(RSS-WSNs).Thisalgorithmmodelsu

    5、nknownmultiplesourcepositionsasasparsevectorbyconstructingredundantdictionaries.Thus,sourceparameters,suchassourcepositionsandenergy,canbeestimatedby1-normminimization.Tospeedupthealgorithm,ane?ectiveconstructionofmultiresolutiondictionaryisintroduced.Furthermore,toimprovethecapacityofresolvingtwo

    6、sourcesthatareclosetoeachother,theadaptivedictionaryre?nementandtheoptimizationoftheredundantdictionaryarrangement(RDA)areutilized.ComparedtoMLmethods,suchasalternatingprojection,theCSalgorithmcanimprovetheresolutionofmultiplesourcesandreducespatialsamplesofWSNs.Thesimulationsresultsdemonstratethep

    7、erformanceofthisalgorithm.1.IntroductionDOAandTDOAarenotverypracticalforlow-costandlow-powerWSNs.RSScane?ectivelyovercomethelimitationsWirelesssensornetworks(WSNs)[1,2]arewidelyappliedinofDOAandTDOA,thusinc

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