一致性卡尔曼滤波算法及其应用分析-consistent kalman filter algorithm and its application analysis.docxVIP

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一致性卡尔曼滤波算法及其应用分析-consistent kalman filter algorithm and its application analysis.docx

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一致性卡尔曼滤波算法及其应用分析-consistent kalman filter algorithm and its application analysis

RESEARCHONCONSENSUS-BASEDKALMANFILTERINGALGORITHMANDITSAPPLICATIONABSTRACTAlongwiththewirelesssensornetworkmoreandmorewidelyappliedindifferentaspectsofourdailysociallife,fusingthelocalinformationwithnoiseanddifferentuncertaintyreasonablyandeffectivelyisaimportantguaranteethatwirelesssensornetworkcanacquiretrueinformationoftheperceptionobject.Asanoveldistributedinformationfusionalgorithm,Consensus-basedKalmandonotneedfusioncenter,thesensornodesonlyneedtoexchangethelocaldatawithitsneighbornodes,andallthenodescanobtainapproximateandhighaccuracyestimationvalue.Meanwhile,thealgorithm’sconvergencerateisfastandestimationperformanceisgood,communicationrequirementissmall.Wirelesssensornetwork’sapplicabilityandrobustnessofdifferentkindsofcomplexenvironmentisimproved.Thisdissertationfocusesonthedifferentuncertaintyofadjacencynodes’estimatevalueinwirelesssensornetworksandinaccuracymodelortime-varyingnoisesinpracticalapplications.Aquantizationfunctionusedforquantizingtheuncertaintyofadjacencynodes’estimatevalueandaadaptivede-noisingstrategyisproposedusedforimprovingthealgorithm’sestimationperformance.Maincontributionsarestructuredasfollows:Firstly,thewirelesssensornetwork’smodelingmethodandthebasicknowledgeofcomplexnetworkareintroduced;theKalmanfilteringalgorithmandconsensusalgorithminvolvinginconsensus-basedKalmanfilteringalgorithmisalsointroduced,meanwhilesomesimulationsofcorrelationalgorithmpreparedforthefollowingresearchisdone.Secondly,aimingatthedifferentuncertaintyofadjacencynodes’estimatevalueinwirelesssensornetwork,consideringtheeffectofnodedegreeonestimateaccuracy,aquantizationfunctionusedforquantizingtheuncertaintyofadjacencynodes’estimatevalueisproposed.Andthenthequantitativevalueisusedtooptimizetheconsensusprotocolasafusionweightoftheadjacencynodes’estimatevalue.Theeffectivenessofthenovelalgorithmisprovedbysimulationsofmobiletargettrackingproblemundertheregularnetwork,smallworldnetworkandrandomnetworkthroughchangetheuncertaintyoftherandomselectednodes.Thirdly,AsConse