摘要
针对突发威胁环境下多无人机航迹重构问题,提出了一种改进蚁群算法。该算法构建了综合山地、天气和雷达威胁的新环境模型,并对初始信息素进行差异化处理,从而加速搜索和收敛。启发函数中引入下一节点航迹点与目标点的距离和相邻航迹点转角因子,优化了航迹曲折并缩短了路径长度。同时采用轮盘赌选择原则,提高了随机性和寻优能力。仿真实验表明,改进算法在综合航迹代价、航迹距离和运行时间上分别比传统蚁群算法降低4.3%、16.87%和30.87%,与文献[12]相比也分别降低了4.1%、2.9%和10.3%,验证了其在多无人机协同规避威胁航迹规划中的高效性与优化效果。
An improved ant colony algorithm is proposed for the problem of multi-UAV trajectory reconstruction in the sudden threat environment.This algorithm constructs a new environmental model that integrates terrain,weather,and radar threats,and applies differentiated initial pheromone processing to accelerate the search and convergence.The heuristic function introduces the distance between the next node trajectory point and the target,as well as the turning factor between adjacent trajectory points,thereby optimizing the trajectory curvature and shortening the path length.Additionally,the roulette wheel selection principle is employed to enhance randomness and search ability.Simulation experiments demonstrate that the modified algorithm reduces the comprehensive trajectory cost,trajectory distance,and running time by 4.3%,16.87%,and 30.87%,respectively,compared to the traditional ant colony algorithm.Compared to the modified ant colony algorithm in literature[12],it achieves reductions of 4.1%,2.9%,and 10.3%respectively,confirming its high efficiency and optimization performance in multi-UAV collaborative threat avoidance trajectory planning.
作者
王秀红
黄子健
方欢
袁雪峰
李凯瑞
WANG Xiuhong;HUANG Zijian;FANG Huan;YUAN Xuefeng;LI Kairui(School of Management Engineering,Zhengzhou University of Aeronautics,Zhengzhou 450046,China)
出处
《物流科技》
2025年第11期7-11,共5页
Logistics Sci Tech
基金
国家自然科学基金项目(72304253)
河南省科技攻关项目(222102210329)
河南省教育厅人文社科一般项目(2021-ZZJH-410、2024-ZZJH-040)。
关键词
突发威胁环境
多无人机
改进蚁群算法
航迹规划
协同规划
航迹重构
sudden threat environment
multi-UAV
improve ant colony algorithm
track planning
collaborative planning
track reconstruction
