Modified unscented Kalman filter using modified filter gain and variance scale factor for highly maneuvering target tracking

查看全文 作　　者：Changyun [1,2]Liu;Penglang [1]Shui;Gang [2]Wei;Song [2]Li

机构地区：[1]National Laboratory of Radar Signal Processing, Xidian University;[2]College of Air and Missile Defense, Air Force Engineering University

出　　处：《Journal of Systems Engineering and Electronics》索引2014年第25卷第3期,共6页

基　　金：supported by the National Natural Science Fundationof China(61102109) 摘　　要：To improve the low tracking precision caused by lagged filter gain or imprecise state noise when the target highly maneuvers, a modified unscented Kalman filter algorithm based on the improved filter gain and adaptive scale factor of state noise is presented. In every filter process, the estimated scale factor is used to update the state noise covariance Qk, and the improved filter gain is obtained in the filter process of unscented Kalman filter(UKF)via predicted variance Pk|k-1, which is similar to the standard Kalman filter. Simulation results show that the proposed algorithm provides better accuracy and ability to adapt to the highly maneuvering target compared with the standard UKF. 关键词：卡尔曼滤波器机动目标跟踪比例因子无迹卡尔曼滤波协方差增益修改状态噪声

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Modified unscented Kalman filter using modified filter gain and variance scale factor for highly maneuvering target tracking

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耦合文献(122)

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