﻿ 基于ICP的稳态部分可辨编队目标精细跟踪算法<sup>*</sup>
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Refined tracking algorithm for steady partly resolvable group targets based on ICP
WANG Cong, WANG Haipeng, HE You, GUO Chen
Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China
Received: 2016-05-19; Accepted: 2016-06-20; Published online: 2016-08-23 16:39
Foundation item: National Natural Science Foundation of China (91538201)
Corresponding author. WANG Cong, E-mail: congnavy@hotmail.com
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

1 ICP基本思想

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2 基于ICP的编队成员关联

2.1 点航映射关联

1) pn，则编队目标存在漏观测。

2) p=n，不确定关系。

3) p>n，则量测中一定存在杂波。

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2.2 旋转与平移参数估计

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Tl′=0时，即

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2.3 关联算法流程

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3 编队成员航迹的状态更新 3.1 漏关联量测填补

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3.2 基于多模型的滤波更新

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4 算法仿真验证与分析

4.1 仿真环境

4.2 仿真结果与分析

1) 在仿真环境1中，雷达视域内共存在2个编队合计9批目标，所有目标的真实运动态势如图 1所示。

 图 1 目标整体态势(环境1) Fig. 1 Overall situation of targets (Environment 1)

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 图 2 平均可行航迹批数比较(环境1) Fig. 2 Comparison of average number of feasible track (Environment 1)

 图 3 y轴位置、速度的均方根误差比较(环境1) Fig. 3 Comparison of position and speed root mean square error at y axes (Environment 1)

2) 在仿真环境2中，雷达视域内共存在一个编队合计5批目标，所有目标的真实运动态势如图 4所示。

 图 4 目标整体态势(环境2) Fig. 4 Overall situation of targets (Environment 2)

 % 算法 第1次拓扑变化 第2次拓扑变化 ICP 88.5 63.4 TM 81.2 45.5 MHT 84.9 50.7

3) 在仿真环境3中，各算法对稀疏编队与密集编队的平均处理时间如表 2所示。

 ms 算法 稀疏编队 密集编队 ICP 0.516 0.477 TM 0.438 0.401 MHT 0.985 0.794

5 结论

1) 采用循环迭代方式实现点航关联的最优匹配，提高了编队成员关联的准确性。

2) 在编队成员航迹的状态更新中采用滑窗α/β逻辑的漏关联量测填补技术，有效提高了在部分可辨条件下的航迹维持问题。

3) 采用非抢占式的多模型滤波更新方法，有效提高了编队内对交叉航迹的正确跟踪率。

4) 经过仿真验证，ICP算法对稳态部分可辨编队具有较高的跟踪可靠性与跟踪精度，且在编队出现交叉航迹时仍具有较高的有效性。

5) 具有较高的处理效率，算法实时性较好。

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#### 文章信息

WANG Cong, WANG Haipeng, HE You, GUO Chen

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

Journal of Beijing University of Aeronautics and Astronsutics, 2017, 43(6): 1123-1131
http://dx.doi.org/10.13700/j.bh.1001-5965.2016.0421