基于迭代离散度序贯检测的航迹抗差关联算法

doi:10.12305/j.issn.1001-506X.2022.08.14

摘要/Abstract

摘要：

针对批处理关联方式对航迹整体信息利用不足以及现有抗差算法无法实现大系统误差下的关联等问题, 提出一种基于迭代离散度序贯检测的航迹抗差关联算法。该算法首先引入迭代离散度作为关联统计量, 并根据基于误差重构的随机量测量推导得到不同时刻离散度的概率分布; 然后根据检测终点的不同设计了两种关联判定准则, 在不同判定准则下进行离散度的序贯检测实现航迹的抗差关联。实验结果表明, 算法在密集目标、大系统误差等复杂场景下均有较高的正确关联率, 并且较常规算法关联速度提升明显。

关键词: 航迹关联, 序贯检测, 系统误差, 离散度

Abstract:

Aiming at the shortcoming of the batch correlation method's insufficient utilization of the overall track information and the existing anti-bias algorithm's inability to deal with the correlation under large system errors, an anti-bias track association algorithm based on sequential detection of iterative discrete degree is proposed. Firstly, the iterative discrete degree is introduced as the correlation statistic, and the probability distribution of discrete degree at different times is derived from the random measurement based on error reconstruction. Then two correlation criteria are designed according to the different detection endpoints, and the sequential detection of discrete degree is carried out under different criteria to realize the anti-bias correlation of tracks. Experimental results show that the algorithm has a high correct correlation rate in complex scenes such as dense targets and large systematic errors, and the correlation speed is significantly improved compared with the conventional algorithm.

Key words: track association, sequential detection, systematic error, discrete degree

中图分类号:

V243.2

关欣, 国佳恩. 基于迭代离散度序贯检测的航迹抗差关联算法[J]. 系统工程与电子技术, 2022, 44(8): 2498-2505.

Xin GUAN, Jia'en GUO. Anti-bias track association algorithm based on sequential detection of iterative discrete degree[J]. Systems Engineering and Electronics, 2022, 44(8): 2498-2505.

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参数	检测阈值
参数	0.80	0.85	0.90	0.95
关联时间/s	1.26	1.47	1.82	1.93
正确关联率	0.921	0.933	0.947	0.975

测距误差/m	测角误差/(°)	正确关联率
测距误差/m	测角误差/(°)	本文算法 (准则1)	本文算法 (准则2)	文献[19] 算法	文献[26] 算法	文献[27] 算法
50	0.3	0.984	0.981	0.875	0.924	0.985
100	0.3	0.983	0.975	0.870	0.921	0.975
150	0.3	0.972	0.963	0.855	0.911	0.953
50	0.5	0.977	0.960	0.849	0.910	0.936
100	0.5	0.971	0.954	0.827	0.898	0.933
150	0.5	0.963	0.947	0.823	0.903	0.925
50	0.7	0.947	0.936	0.800	0.897	0.918
100	0.7	0.938	0.932	0.784	0.889	0.907
150	0.7	0.932	0.926	0.780	0.891	0.898

观测时间/s	不同算法完成关联所需时间/s
观测时间/s	本文算法准则1	本文算法准则2	文献[19] 算法	文献[26] 算法	文献[27] 算法
20	0.81	0.73	4.31	1.24	4.96
40	1.51	1.33	15.23	1.32	10.79
60	2.30	2.08	32.17	1.33	16.98
80	3.36	2.94	56.19	1.53	22.59
100	4.35	3.35	84.83	1.35	28.94

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