信号处理2025，Vol.41Issue(5)：906-923,18.DOI:10.12466/xhcl.2025.05.010
基于带标签CBMeMBer滤波器的低慢小群目标跟踪改进方法
Improved Tracking Method Based on Labeled Cardinality Balanced Multi-target Multi-Bernoulli Filter for Low,Slow,and Small Group Targets
摘要
Abstract
Group target tracking holds significant research value as a crucial step in countering drone swarm threats.Compared with traditional multi-target tracking algorithms,Random Finite Set(RFS)filtering demonstrates substantial advantages in handling multi-target data association and state estimation.However,in low,slow,and small group target scenarios,existing RFS filtering methods generally fail to account for the impact of group characteristics on tracking,nor do they address the challenges of group target initialization and track information extraction.To address these issues,this paper proposes a tracking method for low,slow,and small group targets,combining group modeling,a labeled Cardinality Balanced Multi-target Multi-Bernoulli(CBMeMBer)filter,and adaptive target birth intensity techniques.First,the group target structure was modeled using the virtual leader-follower model and an undirected graph adjacency matrix.Subsequently,a three-level priority label assignment strategy was introduced to improve the traditional labeled CBMeMBer filter,to solve the track ambiguity caused by label conflicts and enhance both tracking accuracy and algorithm efficiency.Additionally,an adaptive target birth intensity algorithm based on the group target scenario and a two-point initialization method was designed to achieve adaptive initialization of new group targets in the RFS framework.Finally,simulation experiments and experiments based on real measured data from the holographic staring radar demonstrated that the proposed method excels in target state estimation and track quality.The tracking performance was superior to those of comparison algorithms,including the traditional labeled CBMeMBer filter,effectively avoiding track crossing and ambiguity,thereby fully showcasing its potential and practical application value in the fine tracking of low,slow,and small group targets.关键词
低慢小目标/随机有限集/群目标跟踪/带标签势均衡多目标多伯努利滤波器/全息凝视雷达Key words
low,slow and small target/random finite set/group target tracking/labeled Cardinality Balanced Multi-target Multi-Bernoulli filter/holographic staring radar分类
信息技术与安全科学引用本文复制引用
钟展鸣,宋强,张月,陈泽彬,杨珺瑶..基于带标签CBMeMBer滤波器的低慢小群目标跟踪改进方法[J].信号处理,2025,41(5):906-923,18.基金项目
国家自然科学基金(U2133216) （U2133216）
广东省科学技术厅先进智能感知技术重点实验室科技规划项目(2023B1212060024) The National Natural Science Foundation of China(U2133216) （2023B1212060024）
Science and Technology Planning Project of Key Laboratory of Advanced IntelliSense Technology,Guangdong Science and Technology Department(2023B1212060024) （2023B1212060024）
