近距空中支援中无人机目标分配问题研究
Research on Target Allocation of Multiple UAV in CAS
吴立冬 1李宗璞 1彭岳松 2熊子涵3
作者信息
- 1. 空军工程大学装备管理与无人机工程学院,西安,710051
- 2. 空军工程大学空管领航学院,西安,710051
- 3. 空军工程大学防空反导学院,西安,710051
- 折叠
摘要
利用无人机实施近距空中支援作战是当前研究的重点,需针对复杂战场环境对实行多目标火力打击的无人机进行路径优化与目标分配.综合考虑无人机飞行高度、不同武器挂载、目标类型及各项指标、威胁区威胁代价、作战时间代价等因素,构建目标毁伤综合指标提高非对称打击效能,设置威胁区安全阈值提高路径有效性分析,采取自适应权重粒子群协同优化算法求解单无人机单目标航迹总代价,采取 0-1 规划法求解多无人机对多目标的不平衡任务分配方案,为近距空中支援任务中多无人机对多目标的分配提供决策支撑.
Abstract
Operation utilized by air support of drones at a close range is currently a research focus.The path and target allocation of Unmanned Aerial Vehicles(UAVs)for multi target firepower strikes require optimization under conditions of complex battlefield environments,and the following factors,such as UAV flight altitude,different weapon mounts,target types and various indicators,threat cost in threat zones,and operational time cost,should be taken into account.A comprehensive target damage index is constructed to improve asymmetric strike effectiveness,and a threat zone security threshold is set to im-prove path effectiveness analysis.The total cost of the optimal trajectory is planned by adopting the Adap-tive Weighted Particle Swarm Collaborative Optimization(APSCO)algorithm for a single drone and a sin-gle target,and the imbalanced task allocation scheme is completed by adopting the 0-1 programming meth-od for multiple drones against multiple targets,providing decision support for the allocation of multiple un-manned aerial vehicles to multiple targets at a close range in performing air support tasks.
关键词
近距空中支援/多无人机/多目标/目标分配/自适应权重粒子群协同优化算法Key words
close air support/multiple drones/multiple targets/target allocation/APSCO引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据