北京航空航天大学学报 ›› 2017, Vol. 43 ›› Issue (6): 1123-1131.doi: 10.13700/j.bh.1001-5965.2016.0421

• 论文 • 上一篇    下一篇

基于ICP的稳态部分可辨编队目标精细跟踪算法

王聪, 王海鹏, 何友, 郭晨   

  1. 海军航空工程学院 信息融合技术研究所, 烟台 264001
  • 收稿日期:2016-05-19 出版日期:2017-06-20 发布日期:2016-09-12
  • 通讯作者: 王聪,E-mail:congnavy@hotmail.com E-mail:congnavy@hotmail.com
  • 作者简介:王聪 男,博士,讲师。主要研究方向:目标跟踪、航迹关联;王海鹏 男,博士,讲师。主要研究方向:群目标跟踪、航迹关联;何友 男,教授,中国工程院院士。主要研究方向:雷达信号处理、信息融合。
  • 基金资助:
    国家自然科学基金(91538201)

Refined tracking algorithm for steady partly resolvable group targets based on ICP

WANG Cong, WANG Haipeng, HE You, GUO Chen   

  1. Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China
  • Received:2016-05-19 Online:2017-06-20 Published:2016-09-12
  • Supported by:
    National Natural Science Foundation of China (91538201)

摘要: 针对稳态编队在部分可辨条件下精细跟踪的难题,提出了一种基于迭代就近点 (ICP)的稳态部分可辨编队精细跟踪算法。首先将ICP算法思想应用于编队成员拓扑的点航关联中,将k时刻的位置状态估计通过最近点循环迭代逼近k+1时刻的量测,在关联判决时采用双门限原则应对部分可辨所带来的漏观测问题,以提高关联时的容错性能;进而采用概率最近邻对漏观测航迹进行填补,以进一步保证跟踪的可靠性;最后,采用多模型法实现编队成员航迹滤波更新,以保证航迹的跟踪滤波精度。仿真结果表明,与现有的基于模版匹配的编队目标跟踪算法以及经典的多假设多目标跟踪算法相比,该算法具有较高的跟踪可靠性与精度,且在编队拓扑发生缓慢变化时具有更高的正确跟踪率。

关键词: 部分可辨, 稳态编队目标, 迭代就近点(ICP), 双门限, 编队拓扑

Abstract: To deal with the problem of the refined tracking of steady groups in partly resolvable condition, a refined tracking algorithm based on iterative closest point (ICP) is proposed in this paper. First, the ICP algorithm is used in tracking association, and by using closest point cyclic iteration, the measurements at time k+1 can be matched with the position estimation at time k. In order to deal with the problem of leakage tracks brought by partly resolvable group and to increase the fault tolerant performance in tracking association, double threshold principle is used in decision making. Then, to further ensure the reliability of tracking, probabilistic nearest neighbor method has been used to fill the leakage tracks. Finally, to ensure the precision of tracking, multi-model algorithm is used to realize filter update of group member tracking. The simulation results show that, compared with group target tracking algorithm based on template matching and classical multiple hypothesis tracking algorithm, the algorithm has better performance in tacking reliability and precision, and can be more accurate when slow change of group topology happens.

Key words: partly resolvable, steady group targets, iterative closest point(ICP), double threshold, group topology

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