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1、TargetLocationEstimationinWirelessSensorNetworksUsingBinaryDataRuixinNiuandPramodK.Varshney1DepartmentofElectricalEngineeringandComputerScience121LinkHallSyracuseUniversitySyracuse,NY13244e-mail:rniu{varshney}@ecs.syr.eduAbstract—Basedontheassumptionthat
2、there-itisimportanttolimitthecommunicationwithinthenetwork.ceivedsignalintensityisinverselyproportionaltoaTherefore,itisdesirablethatonlybinarydataaretransmit-polynomialfunctionofthedistancefromthetarget,tedfromlocalsensorstotheprocessingnode(fusioncente
3、r).amaximumlikelihood(ML)targetlocationestima-Motivatedbythis,weproposeanenergybasedMLtargetlocationestimationmethodusingonlybinarydata.Asanat-torthatusesmulti-framebinarydataisproposedforuralextension,MLestimatorsusingmulti-bitdiscretedatawirelesssensor
4、networks(WSNs).Simulationresultsarealsoinvestigated.showthatthisestimatorismuchmoreaccuratethanaheuristicweightedaveragemethod,anditcanreachII.ProblemFormulationtheCram′er-Raolowerbound(CRLB)evenwithrel-ativelysmallamountofdata.Asanaturalextension,Itisil
5、lustratedinFig.1thatthesignalintensityattenu-theestimatorthatusesmulti-framemulti-bitdiscreteatesasthedistancefromthetargetincreases.Notethatourdataisdeveloped,anditscorrespondingCRLBisde-methodcanhandleanysensordeploymentpatternandtheuniformsensordeploy
6、mentshowninFig.1isonlyaspecialrived.Itstheoreticalperformancebound(CRLB)iscase.Further,wemakethefollowingassumptions:comparedwiththeCRLBoftheestimatorusingana-logdata,whichisalsoderivedinthispaper.Underacommunicationconstraint,guidelinesonanoptimal?Atarg
7、ethasbeencorrectlydetectedinasensor?eldtradeo?betweennumberofbitsandnumberofframeswithNsensors,whoselocationsareknown.areprovidedforvarioussituations.?Weadoptanisotropicsignalintensityattenuationmodel:I.Introduction2P0ai=n(1)Manyaspectsofwirelesssensorne
8、tworks(WSNs)have1+αdigainedextensiveattentioninthepastseveralyears.Thesewhereaiisthesignalamplitudeattheithsensor,P0isincludenetworkarchitectures,routingprotocols,distributedthesignalenergyatdistancezero,anddiisthedistance
