有限视距多传感器集群目标可扩展跟踪方法  

A Scalable Method for Group Target Tracking Using Multisensor with Limited Field of Views

作　　者：张栩琪 周彬 刘海琪 廖骥 刘永旭 杨光 ZHANG Xuqi;ZHOU Bin;LIU Haiqi;LIAO Ji;LIU Yongxu;YANG Guang(Science and Technology on Electronic Information Control Laboratory,Chengdu 610036,China;School of Mathematics,Sichuan University,Chengdu 610065,China)

机构地区：[1]电子信息控制重点实验室,成都610036 [2]四川大学数学学院,成都610065

出　　处：《雷达学报（中英文）》2024年第6期1220-1238,共19页Journal of Radars

基　　金：国家部委基金。

摘　　要：在实际应用中,单传感器的视距、计算资源通常是有限的,多传感器网络的发展和应用为解决具有挑战性的目标跟踪问题提供了更多的可能性。相比于多目标跟踪,集群目标跟踪由于群内目标距离近、协同运动、数目多以及集群分裂合并等因素,会面临更具挑战性的数据关联和计算上的问题,而这些问题在多传感器融合系统中会进一步复杂化。针对有限视距情形下的多传感器集群目标跟踪问题,该文提出了一种可扩展的多传感器集群目标信念传播跟踪方法。该方法在贝叶斯框架下考虑集群结构的不确定性,构建多传感器集群目标联合后验概率密度分解和相应的因子图,以及通过在设计的因子图上运行信念传播算法高效求解数据关联问题。此外,该方法具有计算处理可扩展性,其计算复杂度与传感器数目、集群划分数目和观测数目呈线性关系,与目标数目呈二次关系。最后,仿真实验对比了不同方法关于GOSPA和OSPA(2)的性能,结果表明所提方法能够无缝跟踪集群目标和非群目标、充分利用多传感器信息互补优势、提升跟踪精度。In practical applications,the field of view and computation resources of an individual sensor are limited,and the development and application of multisensor networks provide more possibilities for solving challenging target tracking problems.Compared with multitarget tracking,group target tracking encounters more challenging data association and computation problems due to factors such as the proximity of targets within groups,coordinated motions,a large number of involved targets,and group splitting and merging,which will be further complicated in the multisensor fusion systems.For group target trackingunder sensors with limited field of view,we propose a scalable multisensor group target tracking method via belief propagation.Within the Bayesian framework,the method considers the uncertainty of the group structure,constructs the decomposition of the joint posterior probability density of the multisensor group targets and corresponding factor graph,and efficiently solves the data association problem by running belief propagation on the devised factor graph.Furthermore,the method has excellent scalability and low computational complexity,scaling linearly only on the numbers of sensors,preserved group partitions,and sensor measurements,and scaling quadratically on the number of targets.Finally,simulation experiments compare the performance of different methods on GOSPA and OSPA(2),which verify that the proposed method can seamlessly track grouped and ungrouped targets,fully utilize the complementary information among sensors,and improve tracking accuracy.

关 键 词：多传感器融合 有限视距 集群目标跟踪 可扩展性 信念传播 

分 类 号：TN957[电子电信—信号与信息处理]