简介：Satisfactoryresultscannotbeobtainedwhenthreedimensional(3D)targetswithcomplexmaneuveringcharacteristicsaretrackedbythecommonlyusedtwo-dimensionalcoordinatedturn(2DCT)model.Toaddresstheproblemof3Dtargettrackingwithstrongmaneuverability,onthebasisofthemodifiedthree-dimensionalvariableturn(3DVT)model,anadaptivetrackingalgorithmisproposedbycombiningwiththecubatureKalmanfilter(CKF)inthispaper.Throughideologyofreal-timeidentification,theparametersofthemodelarechangedtoadjustthestatetransitionmatrixandthestatenoisecovariancematrix.Therefore,statesofthetargetarematchedinreal-timetoachievethepurposeofadaptivetracking.Finally,foursimulationsareanalyzedindifferentsettingsbytheMonteCarlomethod.Allresultsshowthattheproposedalgorithmcanupdateparametersofthemodelandidentifymotioncharacteristicsinreal-timewhentargetstrackingalsohasabettertrackingaccuracy.