Bearing-only underwater uncooperative target tracking for non-Gaussian environment using fast particle filter

被引:0
|
作者
Hou, Xianghao [1 ,2 ]
Yang, Long [1 ,2 ]
Yang, Yixin [1 ,2 ]
Zhou, Jianbo [1 ,2 ]
Qiao, Gang [3 ]
机构
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Shaanxi, Peoples R China
[2] Shaanxi Key Lab Underwater Informat Technol, Xian, Shaanxi, Peoples R China
[3] Harbin Engn Univ, Coll Underwater Acoust Engn, Harbin, Heilongjiang, Peoples R China
来源
IET RADAR SONAR AND NAVIGATION | 2022年 / 16卷 / 03期
关键词
adaptive Kalman filters; adaptive estimation; particle filtering (numerical methods); sonar tracking; tracking filters; KALMAN FILTER; SONAR; OBSERVABILITY; STATE;
D O I
10.1049/rsn2.12198
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Bearing-only tracking of an underwater uncooperative target is essential to defend the sea territory. Considering the influences by uncertain underwater environment, the purpose of this work is to estimate 2-D locations and velocities of an interested underwater target for non-Gaussian environment. In this work, a fast particle filter (FPF) based on the traditional particle filter (PF) with novel jet transport (JT) technique is proposed to deal with this problem. Aiming to overcome the heavy computation burden of the traditional PF that limits most of its practical applications, the JT technique can dramatically reduce the computation time and complexity in the particle evolution process, which contributes huge computational complexities to the traditional PF. Then, the proposed FPF is tested through simulations in the 2-D underwater uncooperative target tracking scenario. Finally, the Monte Carlo simulation results demonstrate that the proposed FPF can track the underwater uncooperative target with the similar accuracies as the traditional PF but only occupies less than 20% of the computational resources.
引用
收藏
页码:501 / 514
页数:14
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