系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (6): 1905-1912.doi: 10.12305/j.issn.1001-506X.2026.06.12

• 传感器与信号处理 • 上一篇    下一篇

基于LMB滤波的分布式多传感器多目标跟踪

王志伟(), 蔡兴雨, 徐伟(), 严超   

  1. 西安电子工程研究所,陕西 西安 710100
  • 收稿日期:2024-10-15 修回日期:2024-12-17 接受日期:2026-04-13 出版日期:2026-06-25 发布日期:2025-07-03
  • 通讯作者: 徐伟 E-mail:572229144@qq.com;xuweibeall@126.com
  • 作者简介:王志伟(1988—),男,高级工程师,博士,主要研究方向为雷达目标跟踪、分布式统计信息融合
    蔡兴雨(1967—),男,研究员,硕士,主要研究方向为武器系统设计和雷达信号处理
    严 超(1983—),男,研究员,硕士,主要研究方向为雷达系统设计和雷达信号处理
  • 基金资助:
    国家自然科学基金(61901498,61871384,61921001)资助课题

Distributed multi-sensor multi-target tracking based on LMB filter

Zhiwei WANG(), Xingyu CAI, Wei XU(), Chao YAN   

  1. Xi’an Electronic Engineering Research Institute,Xi’an 710100,China
  • Received:2024-10-15 Revised:2024-12-17 Accepted:2026-04-13 Online:2026-06-25 Published:2025-07-03
  • Contact: Wei XU E-mail:572229144@qq.com;xuweibeall@126.com

摘要:

基于标签多伯努利(label multi-Bernoulli,LMB)后验密度的多传感器多目标跟踪方法存在“标签不一致”、航迹连续性差,漏检率和跳变率高等问题。对此,提出一种基于LMB后验航迹估计的分布式多传感器多目标跟踪方法。首先建立最小化不同传感器估计航迹间多帧状态差异和时间维关联跳变的目标函数,采用凸松弛技术将高维非线性目标函数化简为线性形式,通过聚类和线性规划在多项式时间内实现了航迹的有效关联。其次采用广义协方差交集准则和互补原则并行融合关联航迹。最后基于有限集统计学理论推导了非关联航迹的融合方法。仿真实验表明所提方法可有效提升航迹连续性、降低航迹漏检和跳变,具有较好的工程应用价值。

关键词: 标签随机有限集, 航迹关联, 凸松弛, 广义协方差交集

Abstract:

The multi-sensor multi-target fusion tracking method based on label multi-Bernoulli (LMB) posterior density has problems, such as label inconsistency, high miss-detection and track switches, and poor continuity. To address this problem, a distributed multi-sensor multi-target tracking method is developed based on LMB posterior trajectory estimation. Firstly, the objective function is established to minimize the multi-frame state difference and time dimension correlation switches between tracks estimated by different sensors. The convex relaxation technique is used to simplify the high-dimensional nonlinear objective function into a linear form, and the effective correlation of tracks is achieved in polynomial time through clustering and linear programming. Then, the generalized covariance intersection criterion and complementarity principle are used to fuse correlated trajectories in parallel. Finally, a fusion method for un-correlated trajectories is derived based on finite set statistics. Simulation experiments show that the proposed method effectively improves trajectory continuity and reduces trajectory missed-detections and switches, verifying its fine engineering application value.

Key words: label random finite set, tracks correlation, convex relaxation, generalized covariance intersection

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