摘要
为了改善实际跟踪过程中因为缺乏目标先验信息造成的模型失配对滤波器跟踪性能造成的影响,引入强跟踪滤波(STF)思想对渐进更新扩展Kalman滤波(PU-EKF)算法进行改进,提出了强跟踪渐进更新扩展Kalman滤波(STPU-EKF)算法。在多种模型失配情况下进行磁偶极子跟踪仿真试验,对所建算法的性能进行验证,仿真结果表明:所建立的STPU-EKF算法兼具PU-EKF和STF算法的优点,具有较高的准确性和较好的鲁棒性。
In view of the influence of model mismatch caused by lack of prior information of the target on the tracking performance of the filter in the actual tracking process,the idea of strong tracking filtering(STF)was introduced to improve the asymptotic extended Kalman filtering algorithm,and hence a strong tracking asymptotic extended Kalman filtering(STPEKF)algorithm was proposed.The performance of the proposed algorithm was verified by magnetic dipole tracking simulation test under various model mismatches.The simulation results show that the STPEKF algorithm has the advantages of both PEKF and STF algorithms,with high accuracy and good robustness.
作者
单珊
周穗华
戴忠华
张宏欣
SHAN Shan;ZHOU Sui-hua;DAI Zhong-hua;ZHANG Hong-xin(College of Weaponry Engineering, Naval Univ. of Engineering, Wuhan 430033, China;Unit No. 91439, Dalian 116041, China)
出处
《海军工程大学学报》
CAS
北大核心
2022年第1期105-112,共8页
Journal of Naval University of Engineering
关键词
目标跟踪
模型失配
强跟踪滤波器
鲁棒性
target tracking
model mismatch
strong tracking filter
robust
