面向山地环境的多无人机协同搜索攻击算法  

A collaborative search attack algorithm for multiple UAVs in mountain environments

作　　者：姚明辉 师聪 牛燕 吴启亮 王聪[1] YAO Minghui;SHI Cong;NIU Yan;WU Qiliang;WANG Cong(School of Aeronautics and Astronautics,Tiangong University,Tianjin 300387,China;School of Control Science and Engineering,Tiangong University,Tianjin 300387,China)

机构地区：[1]天津工业大学航空航天学院,天津300387 [2]天津工业大学控制科学与工程学院,天津300387

出　　处：《兵器装备工程学报》2025年第3期162-172,共11页Journal of Ordnance Equipment Engineering

基　　金：国家自然科学基金项目(11972253);天津市自然科学基金项目(23JCZDJC00230)。

摘　　要：针对多无人机在不规则山地环境下协同搜索攻击未知目标的问题,设计了一种基于蚁群优化算法(ACO)与向量直方图法(VFH)的无人机群智能自组织协同搜索攻击(IACO-VFH)算法。首先,以最大化搜索效率和攻击数量为目标建立了协同搜索攻击优化模型。其次,在协同搜索过程中先通过VFH方法计算无人机当前位置的代价函数,再利用代价函数改进ACO算法中的启发式函数,以提高无人机的避障性能。然后,使用信息素扩散更新与动态化递增因子来改进ACO算法中的信息素更新机制,在提升局部避障性能的同时有效兼顾搜索覆盖率。最后,仿真结果表明:在简单圆形障碍物环境中,IACO-VFH算法的平均覆盖率与平均摧毁目标数量分别比粒子群优化方法高出11.79%与2.46个,同时,在不规则山体环境中,IACO-VFH算法在保证无人机自身安全的同时,能够有效地搜索战场环境中的未知静态和动态目标。In order to cope with the problem of multi-UAV cooperative search and attack on unknown targets in the environment with irregular mountainous obstacles,an intelligent self-organizing cooperative search attack algorithm for UAV swarm(IACO-VFH)based on ant colony optimization algorithm(ACO)and vector histogram method(VFH)is designed.Firstly,a collaborative search attack optimization model is established with the goal of maximizing the search efficiency and the number of attacks.Secondly,in the process of cooperative search,VFH method is used to calculate the cost function,and then improve the heuristic function in the ACO algorithm using the cost function to enhance the obstacle avoidance performance of the UAV.Then,the pheromone diffusion update and dynamic increment factor are used to improve the pheromone update mechanism in the ACO algorithm,effectively balancing search coverage while improving local obstacle avoidance performance.Finally,the simulation results show that in a simple circular obstacle environment,the IACO-VFH algorithm achieves an average coverage rate and average number of targets destroyed that are 11.79%and 2.46 targets higher,respectively,compared to the particle swarm optimization.At the same time,in the irregular mountainous terrain,the IACO-VFH algorithm can effectively search for unknown static and dynamic targets in the battlefield environment while ensuring the flight safety of the UAV.

关 键 词：多无人机 山地环境 协同搜索攻击 蚁群优化 向量直方图 

分 类 号：V279[航空宇航科学与技术—飞行器设计]