基于身份匈牙利算法的无人机蜂群分布式目标分配方法  

Distributed Target Assignment Method for UAV Swarms Using Identity Hungarian Algorithm

作　　者：刘兴宇 郭荣化 任成才 闫超 常远 周晗 相晓嘉[2] LIU Xingyu;GUO Ronghua;REN Chengcai;YAN Chao;CHANG Yuan;ZHOU Han;XIANG Xiaojia(Unit 32399 of PLA,Nanjing 210046,Jiangsu,China;College of Intelligence Science and Technology,National University of Defense Technology,Changsha 410073,Hunan,China;Academy of Military Sciences,Beijing 100091,China)

机构地区：[1]32399部队,江苏南京210046 [2]国防科技大学智能科学学院,湖南长沙410073 [3]军事科学院,北京100091

出　　处：《兵工学报》2023年第9期2824-2835,共12页Acta Armamentarii

摘　　要：对敌方多目标实施分布式打击是无人机蜂群的重要作战样式,无人机个体如何选择打击目标是其中的关键问题之一。现有目标分配算法大多针对信息全局可知的集中式目标分配问题,无法适应局部感知交互的战场环境。基于就近原则以及目标价值原则,参考目标距离、目标方位角、目标价值、无人机速度等要素,在匈牙利算法(HA)的基础上考虑了无人机身份和目标身份信息,提出了身份HA,实现了无人机蜂群的分布式目标分配。算例分析结果表明,身份HA可以避免无人机蜂群遗漏目标或冗余攻击,提升无人机蜂群的整体作战效能,为实现鱼贯依次打击的作战策略奠定算法基础。Distributed strike capabilities against multiple enemy targets are crucial for Unmanned Aerial Vehicle(UAV)swarms in combat scenarios.One key challenge is how individual UAVs choose their targets for effective strikes.Most existing target allocation algorithms are designed for centralized target allocation problems with global information,making them unsuitable for battlefield environments with local perception and interaction.To address this,we propose the Identity Hungarian Algorithm,which incorporates drone and target identities into the traditional Hungarian algorithm.This approach considers factors such as proximity,target value,target distance,target azimuth,and UAV speed to achieve distributed target allocation for UAV swarms.Case study results demonstrate that the proposed identity Hungarian Algorithm mitigates target omission and redundancy attacks,enhances the overall combat effectiveness of the UAV swarm,and lays the foundation for effective combat strategies in sequence.

关 键 词：无人机蜂群 分布式目标分配 匈牙利算法 打击优势 

分 类 号：E911[军事]