针对区域防御的多无人机序列捕捉算法  

Multi-UAV Sequential Capture Algorithm for Area Defense

作　　者：何子琦 李博宸 王成罡 宋磊 HE Ziqi;LI Bochen;WANG Chenggang;SONG Lei(School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《兵工学报》2025年第4期279-291,共13页Acta Armamentarii

基　　金：上海交通大学深蓝计划项目(SL2022MS010);国防科技重点实验室基金项目(2022JCJQLB03308);国家自然科学基金项目(62303316)。

摘　　要：针对区域防御任务中多个入侵者的拦截问题,考虑追捕任务间时序关系与总体拦截效能,提出一种多无人机序列捕捉算法。基于任务的长期规划收益与短期执行效果构建任务的时序收益与空间收益,分别作为任务分配和任务执行的优化目标,实现复杂博弈问题的动态实时求解。基于可达集方法描述攻防双方优势程度并构建任务时序收益,引入深度Q网络对其进行估计进而引导任务分配;基于任务空间收益求解单攻击者追逃博弈问题,给出连续动作空间任务执行的最优控制策略。仿真结果表明,所提算法通过优化任务时空收益能够实现多无人机间的有效合作,提升防御方的捕获成功率,并具有较强的可扩展性。For the interception issue of multiple intruders in area defense missions,a multi-UAV sequential capture algorithm is proposed by taking into account the temporal relationship between pursuit tasks and the overall interception effectiveness.The temporal and spatial rewards are constructed based on the long-term planning benefits and short-term execution effects of the tasks,which serve as the optimization objectives for task allocation and execution,respectively,and the dynamic and real-time solutions are achieved for complex game-theoretical problems.A reachability-set-based approach is used to describe the advantage levels of both attackers and defenders,and a deep Q-network is introduced to estimate the temporal rewards for tasks and then guide task allocation.The single attacker pursuitevasion game problem is solved based on the spatial reward of task,and an optimal control strategy is presented for task execution in a continuous action space.Simulated results show that the peoposed algorithm optimizes the temporal and spatial rewards to facilitate the effective cooperation among multiple UAVs,enhances the capture success rate of the defenders,and has an increased scalability.

关 键 词：多无人机 时空任务收益 序列捕捉 时序任务分配 深度Q网络 

分 类 号：V279[航空宇航科学与技术—飞行器设计]