分布式无人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（Unmanned Aerial Vehicle, UAV）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，本文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，所述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。

Distributed 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. Aiming to address the challenge that single swarm’s poor performance 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 method presented in this paper 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.