航空学报 > 2025, Vol. 46 Issue (16): 331635-331635   doi: 10.7527/S1000-6893.2024.31635

面向多目标跟踪的集群无人机自组织共识决策方法

赵江1, 皮明豪1, 田栢苓2, 池沛3(), 王英勋3   

  1. 1.北京航空航天大学 自动化科学与电气工程学院,北京 100191
    2.天津大学 电气自动化与信息工程学院,天津 300072
    3.北京航空航天大学 无人系统研究院,北京 100191
  • 收稿日期:2024-12-09 修回日期:2025-01-03 接受日期:2025-01-09 出版日期:2025-08-25 发布日期:2025-01-16
  • 通讯作者: 池沛 E-mail:peichi@buaa.edu.cn
  • 基金资助:
    中央高校基本科研业务费专项资金资助

Self-organized consensus decision-making method for swarm UAV tracking multiple targets

Jiang ZHAO1, Minghao PI1, Bailing TIAN2, Pei CHI3(), Yingxun WANG3   

  1. 1.School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China
    2.School of Electrical and Information Engineering,Tianjin University,Tianjin 300072,China
    3.Institute of Unmanned System,Beihang University,Beijing 100191,China
  • Received:2024-12-09 Revised:2025-01-03 Accepted:2025-01-09 Online:2025-08-25 Published:2025-01-16
  • Contact: Pei CHI E-mail:peichi@buaa.edu.cn
  • Supported by:
    Fundamental Research Funds for the Central Universities of China

摘要:

分布式无人机(UAV)集群通过自主决策与信息交互,可实现协同跟踪与动态任务分配,在复杂多变的动态目标跟踪控制场景中展现出较大的应用潜力。针对单一无人集群难以对多个分散运动的目标进行有效跟踪的挑战,提出了一种基于信息共识的集群无人机自组织动态决策方法。首先,考虑到无人机间的通信距离约束与通信时延,设计了基于最新时戳转发原则的集群信息共识算法,实现集群无人机的信息共识。其次,提出了基于求助应答的集群协同决策算法,实现了成员调配决策与自组织分组。最后,设计了基于自协调机制的目标跟踪控制算法,实现控制分量权重的自适应调整以及自组织的目标跟踪。与现有关于多目标跟踪的研究相比,提出的方法可在目标跟踪过程中实现动态目标分配决策,可根据各目标的逃逸风险大小确定为各目标分配的无人机数目。仿真结果表明,提出的方法可在目标分散运动时实现集群的自组织分组,分组的无差率在0.9以上。

关键词: 无人机(UAV), 多目标跟踪, 集群信息共识, 协同决策, 自组织

Abstract:

Distributed Unmanned Aerial Vehicle (UAV) swarms can achieve collaborative tracking and dynamic task allocation through autonomous decision-making and information interaction, demonstrating significant application potential in complex and dynamic target tracking control scenarios. To address poor performance of the single swarm in tracking multiple separating moving targets, a self-organized dynamic decision-making method for UAV swarm based on information consensus is proposed. Firstly, considering the communication distance constraints and communication delays between UAVs, a swarm information consensus algorithm based on the latest timestamp forwarding principle is designed to achieve information consensus among UAVs. Secondly, a swarm collaborative decision-making algorithm based on request-response is proposed, realizing member allocation, decision-making and self-organized grouping. Finally, a target tracking control algorithm based on a self-coordination mechanism is designed, achieving adaptive adjustment of control component weights and self-organized target tracking. Compared to existing research on multi-target tracking, the proposed method can realize dynamic target allocation decision-making during the target tracking process and determining the number of UAVs allocated to each target based on the escape risk of each target. Simulation results show that the proposed method can achieve self-organized grouping of the swarm when targets are separating, with a grouping accuracy rate of above 0.9.

Key words: unmanned aerial vehicle (UAV), multi-target tracking, swarm information consensus, collaborative decision-making, self-organizing

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