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

作     者：Changyun Liu Penglang Shui Gang Wei Song Li 

作者机构：National Laboratory of Radar Signal Processing Xidian University College of Air and Missile Defense Air Force Engineering University 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2014年第25卷第3期

页      面：380-385页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Fundationof China(61102109) 

主　　题：unscented Kalman filter （UKF） target tracking filter gain maneuvering target nonlinearity modified unscented Kalman filter （MUKF）. 

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.