Extended target tracking using a Gaussian Mixture PHD filter

Extended target tracking using a Gaussian Mixture PHD filter

ID:39772545

大小:2.60 MB

页数:16页

时间:2019-07-11

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1、1ExtendedTargetTrackingusingaGaussian-MixturePHDfilterKarlGranstrom,¨Member,IEEE,ChristianLundquist,andUmutOrguner,Member,IEEEAbstract—ThispaperpresentsaGaussian-mixtureimplemen-BaumetalhavepresentedtherandomhypersurfacemodeltationofthePHDfilterfortrackingextendedtargets.The[4],anexten

2、dedtargetmodelwhichhasbeenusedtotrackexactfilterrequiresprocessingofallpossiblemeasurementsetelliptictargets[5],aswellasmoregeneralshapes[6].Apartitions,whichisgenerallyinfeasibletoimplement.Amethoddifferentapproachtoelliptictargetmodelingistherandomisproposedforlimitingthenumberofcon

3、sideredpartitionsandpossiblealternativesarediscussed.TheimplementationisusedmatrixframeworkbyKoch[7].Thetargetkinematicalstatesonsimulateddataandinexperimentswithreallaserdata,andaremodeledusingaGaussiandistribution,whiletheellip-theadvantageofthefilterisillustrated.Suitableremediesar

4、esoidaltargetextensionismodeledusinganinverseWishartgiventohandlespatiallyclosetargetsandtargetocclusion.distribution.UsingrandommatricestotrackgrouptargetsIndexTerms—Targettracking,extendedtarget,PHDfilter,underkinematicalconstraintsisdiscussedin[8].Modificationsrandomset,Gaussian-mix

5、ture,lasersensor.andimprovementstotheGaussian-inverseWishartmodelof[7]havebeensuggestedin[9],andthemodel[7]hasbeeninte-I.INTRODUCTIONgratedintoaProbabilisticMulti-HypothesisTracking(PMHT)Inmostmulti-targettrackingapplicationsitisassumedthatframeworkin[10].Acomparisonofrandommatricesa

6、ndtheeachtargetproducesatmostonemeasurementpertimestep.randomhypersurfacemodelundersingletargetassumptionThisistrueforthecaseswhenthedistancebetweentheisgivenin[11].Measurementsoftargetdown-rangeextenttargetandthesensorislargeincomparisontothetarget’sareusedtoaidtrackretentionin[12].

7、Otherapproachestosize.Inothercaseshowever,thetargetsizemaybesuchestimatingthetargetextensionsaregivenin[13]–[15].thatmultipleresolutioncellsofthesensorareoccupiedbyUsingtherigorousfinitesetstatistics(FISST),Mahlerhasthetarget.Targetsthatpotentiallygiverisetomorethanpioneeredtherecenta

8、dvancesinthe

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