Maneuvering target tracking algorithm based on cubature Kalman filter with observation iterated update  

作　　者：胡振涛 Fu Chunling Cao Zhiwei Li Congcong 

机构地区：[1]Instituteof Image Processing and Pattern Recognition,Henan University [2]School of Physics and Electronics,Henan University

出　　处：《High Technology Letters》2015年第1期39-45,共7页高技术通讯（英文版）

基　　金：Supported by the National Nature Science Foundations of China(No.61300214,U1204611,61170243);the Science and Technology Innovation Team Support Plan of Education Department of Henan Province(No.13IRTSTHN021);the Science and Technology Research Key Project of Education Department of Henan Province(No.13A413066);the Basic and Frontier Technology Research Plan of Henan Province(No.132300410148);the Funding Scheme of Young Key Teacher of Henan Province Universities;the Key Project of Teaching Reform Research of Henan University(No.HDXJJG2013-07)

摘　　要：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.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 in- teracting multiple model algorithm based on the cubature Kalman filter with observation iterated up- date 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 mul- tiple model, and the stability and reliability of model identification and state estimation are effective- ly 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.

关 键 词：maneuvering target tracking nonlinear filtering cubature Kalman filter（CKF） interacting multiple model（IMM） 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]