多传感器融合技术小论文Word下载.docx
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多传感器融合技术小论文Word下载.docx
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Targetrecognitionisanimportantelementinthefieldofpatternrecognition,itisalsocalledasidentityestimationorattributeclassification.Fortargetrecognition,themaindifficultyistheextractiontargetcharacteristics.Inthepracticalsystem,themeasurementdataisincomplete,uncertainandfuzzy,soitisverydifficulttodetermineexactlytarget.Thetraditionaltargetrecognitionmethodsincludethefeaturelevelfusion,thedatalevelfusionanddecisionlevelfusionetc.Ofthesemethods,thefuzzymethodisaneffectivemethod.
2.1CorrelationFunction
Inthemulti-sensorsystemXiisthemeasurementdataprovidedbytheithsensor,Xjisthemeasurementdataprovidedbythejthsensor,XiandXjobeyGaussdistribution.Thepdf(probabilitydistributionfunction)curveisregardedascharacteristicfunctionofsensor,pi(x),pj(x).xiisameasurementdataofXi,xjisameasurementdataofXj.
Inordertoreflectthevariationofxiandxj,theconfidencedistancemeasureisinducted,suppose
(1)
(2)
(3)
(4)
dijiscalledastheconfidencedistancemeasureofthemeasurementdataprovidedbytheithsensorandthemeasurementdataprovidedbythejth
sensor,usingerrorfunctionwecandirectlyworkoutdij[1],dijiswrittenasfollows:
(5)
(6)
Iftherearensensorsinthesystem,thenconfidencedistancematrixDnofthemeasurementdataiscomposedoftheconfidencedistancemeasuredij(i,j=1,2,…n),Dniswrittenasfollows:
(7)
Thegenericfusionmethodisbasedonafusionhighlimit
fordij,let
(8)
Ifrij=0,wethinkthattheithsensorandthejthsensorarenotsupporteachother.Ifrij=1,wethinkthatthejthsensorissupportedbytheithsensor.Ifrij=rji,wethinkthattheithsensorandthejthsensoraresupporteachother.Now,theproblemarisesthat
isveryabsoluteandsubjective,thefusionresultsisaffectedbythesubjectivefactor.
Focusedontheproblem,anewmethodisproposedinthepaper.Accordingtotheoperationofdijandthestatisticalsignificanceofoperationalformula,wecanknow
andthevalueofdijissmaller,thesupportabilityofsensorishigher.Accordingtothedefinitionofthecorrelationfunctionofthefuzzytheory,let
(9)
Thevalueofthecorrelationfunctionf(i/j)denotesthesupportabilityofsensor,thecorrelationfunctionisdefinedas:
(10)
Wherei,j=1,2,…,n
Thematrixoff(i/j),Cisformedanditisaphalanx,itsorderisn.
Inordertodeterminethesupportabilityofeachsensorsupportedbyothersensors,let
(11)
isthesupportabilityoftheithsensorsupportedbyothersensors.
2.2FuzzyIntegrationFunction
SupposethatU={1,2,...,j,…,N}isasequencesetwhichiscomposedofNkindsoftargetattributeandS={1,2,…,i,…M}isasequencesetwhichiscomposedofMsensors.mijisthesupportabilityofthejthtargetattributesupportedbytheithsensorand
.Ojdenotesthatthetargetattributeisthejth,thepossibilitydistributionoftargetattributeisdefinedas[2][3][4]:
(12)
Forthegenericharddecision,thatis,thesingleattributeisregardedasthetargetattribute,thiscanberegardedasthespecialcase,thatis,
(13)
Whenthetargetattributeisaset,mijiswrittenas:
(14)
fiisthetrustfunctionofthesensor[6],fiiswrittenas:
(15)
Where
isthereliabilityoftheinformationprovidedbytheithsensor.
ForeachmeasurementdataZ,weusethemembershipfunction
tomappingZtothedegreeofmembership
intheinterval[0,1].Thevalueof
reflectsthereliabilityoftheinformationprovidedbythesensor.Whenthedifferentsensormeasures,wecangainthereliabilityoftheinformationprovidedbythesensorusingtheformula
(16)
Afterwegainthepossibilitydistributionoftargetattribute
,weusethefuzzyintegrationfunctiontocalculatetheMpossibilitydistribution,thenwecangainthefusionresultoftargetattribute.
(17)
Accordingtofuzzyintegrationfunctiontheory,wecangainmf,mfiswrittenasfollows:
(18)
Whereisthefuzzyintegrationfunction.Inthepaper,thefuzzyintegrationfunctioniswrittenasfollows:
(19)
3.EmitterTargetRecognitionBasedonMulti-sensorDataFusionofESMandIR
Theemittertargetrecognitionisplayingmoreandmoreimportantroleinthemodernwar,andtheemittertargetrecognitionisbecomingmoreandmoredifficultbecauseoftheapplicationofthehightechniqueandtheanti-measures.Intheprocessoftheemittertargets’recognition,ifsinglesensorormulti-sensorofsinglekindisused,thedistilledinformationisnotall-sided,sotherecognitionperformanceisnotsogood,especiallyinthecomplexenvironment.
Withtheelectromagneticsignalandinfrared(IR)imagewhichareobtainedbyreconnaissancesatelliteESMsensors(radarandcommunicationEWreconnaissanceequipments)andIRimagesensor,theemittertargetrecognitionmethodbasedonthemultisensorydatafusionisproposedinthispaper.First,accordingtothedifferenceoftheinformationofferedbyESMandIRsensors,thispaperbringsforwardtwomethodstoobtainBPAFseparately:
oneissyntheticfuzzyevaluation;
theotherisgraycorrelationanalysis.SothedifficultproblemofhowtogetBPAFunderdifferentconditionsissolved.Further,thefusionmethodbasedontheD-Sevidencetheoryisdiscussedandwhichisappliedtotheemittertargetrecognition.
3.1TheMethodstoCalculateBPAF
IntheD-Sevidencetheory,therecognitionframeΘindicatestheinterestedpropositionsset.TheBPAFBasicProbabilityAssignmentFunction)basedonΘisdefinedasm:
2Θ→[0,1],whichsatisfies
(20)
WherepropositionAisanonemptysubsetofΘ,m(A)reflectsthereliableextentofA.TheBPAFisthekeyofD-Sevidencetheory.Asto
ESMsystem,theBPAFiscalculatedwithsyntheticfuzzyevaluationaccordingtomultiplefeaturesofthetarget.AstoIRsensorsystem,theBPAFiscalculatedwithgraycorrelationanalysisaccordingtotheIRimagecharacteristicofthetarget.
3.1.1MethodtocalculateBPAFofESMsystem
Todefinethefactorset:
TheobservationoftheESMsystemcommonlyincludethefeaturesdatasuchasRF,PRI,PW,IPCandsoon.InthesyntheticfuzzyevaluationmodelofcalculatingBPAF,thefactorsetisdefinedasthesetofRF,PRI,PW,andIPC.
Togivetheweight:
Intheprocessofevaluatingthereliableextent,thevalueofBPAFisdirectlyrelativetotheweightofallthefeatures.Here,theweightofRF,PRI,PW,andIPCisa1,a2,a3anda4separately,andtheysatisfythestandardizationcondition.
Todefinetheevaluationset:
Forevaluatingthereliableextent,iftheevaluationsetisdefinedasagroupoffuzzylanguage{verygood,good,common,bad,verybad},thentheevaluationresultisratherroughandisdisadvantageoustotherecognition.Here,theevaluationsetisdefinedasarealnumbersetV={x|0≤x≤1}.Thebiggerthevalueofxis,thehigherthereliableextentis,onthecontrary,thesmallerthevalueofxis,thelowerthereliableextentis.
Toevaluatesinglefactor:
TheBPAFofESMsystemiscalculatedwithsyntheticfuzzyevaluationaccordingtomultiplefeaturesofthetarget.Firstofall,thesinglefactoristobeevaluated.
3.1.2MethodtocalculateBPAFofIRsystem
Accordingtothesimilarityordissimilarityof
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