一种利用量测空间聚类的多帧检测前跟踪算法

doi:10.19665/j.issn1001-2400.2021.05.026

摘要/Abstract

摘要：

针对现有多帧检测前跟踪算法在相互临近的多目标场景下运算复杂度高的问题,提出一种利用量测空间聚类的多帧检测前跟踪算法。该算法采用跨多帧构建关联集合,依据关联集合对量测点迹进行标签标记,以获取多目标在量测空间的分布信息,实现多帧量测点迹的聚类划分,并在各聚类内独立地运行多帧检测前跟踪算法。通过大量仿真实验和性能分析表明,该算法的检测性能与现有多帧检测前跟踪算法相当,而运算复杂度大幅降低。

关键词: 目标检测, 聚类, 检测前跟踪, 动态规划

Abstract:

A multi-frame track before detect (TBD) algorithm based on Measurement Space clustering is proposed to solve the high computational complexity problem of the existing multi-frame TBD algorithm in the multiple targets scenario.In the proposed algorithm,a track extrapolation strategy is used to construct an association set among the tracks of continuous data frames,and then a label is constructed according to the association set to obtain the distribution information on multiple targets in the measurement space,a multi-frame measurement points is divided into clusterings,and a multi-frame TBD Algorithm is implemented in each clustering.Simulation result and performance analysis show that the detection performance of the proposed algorithm is comparable to that of the existing multi-frame TBD algorithm,and that the computational complexity is greatly reduced.

Key words: target detection, clustering, track before detect, dynamic programming

中图分类号:

TN953+.7

张佳琦,陶海红,张修社,韩春雷. 一种利用量测空间聚类的多帧检测前跟踪算法[J]. 西安电子科技大学学报, 2021, 48(5): 231-238.

ZHANG Jiaqi,TAO Haihong,ZHANG Xiushe,HAN Chunlei. A multi-frame track before detect algorithm utilizing measurement space clustering[J]. Journal of Xidian University, 2021, 48(5): 231-238.

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算法	状态转移集合	航迹构建
STC-DP-TBD	O(PL[(N_rN_θ-K)F_FAR+KP_d]²)	O(TF^stc4)
MSC-DP-TPD	O(PL[(N_rN_θ-K)F_FAR+KP_d]²)	O(TF^stc)/N

F_FAR	10^-1	10^-2	10^-3
TS-DP-TBD	20.538 6	1.860 1	0.303 3
STC-DP-TBD	98.628 7	5.279 8	0.563 7
MSC-DP-TBD	76.680 8	2.512 5	0.389 1