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Maneuvering target tracking algorithm based on cubature Kalman filter with observation iterated update
Authors:Hu Zhentao  Fu Chunling  Cao Zhiwei  Li Congcong
Institution:1. Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng 475004, P.R.China
2. School of Physics and Electronics, Henan University, Kaifeng 475004, P.R.China
Abstract:Reasonable selection and optimization of a filter used in model estimation for a multiple model structure is the key to improve tracking accuracy of maneuvering target.Combining with the cubature Kalman filter with iterated observation update and the interacting multiple model method,a novel interacting multiple model algorithm based on the cubature Kalman filter with observation iterated update is proposed.Firstly,aiming to the structural features of cubature Kalman filter,the cubature Kalman filter with observation iterated update is constructed by the mechanism of iterated observation update.Secondly,the improved cubature Kalman filter is used as the model filter of interacting multiple model,and the stability and reliability of model identification and state estimation are effectively promoted by the optimization of model filtering step.In the simulations,compared with classic improved interacting multiple model algorithms,the theoretical analysis and experimental results show the feasibility and validity of the proposed algorithm.
Keywords:maneuvering target tracking  nonlinear filtering  cubature Kalman filter (CKF)  interacting multiple model (IMM)
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