基于改进混沌蚁群算法的多机冲突解脱仿真研究  

Simulation Research on Multi-aircraft Conflict Resolution Based on Improved Chaotic Ant Colony Algorithm

作　　者：童亮 杨婕[1,2] 甘旭升 沈堤[1,2] 杨文达 陈达雄[4] Tong Liang;Yang Jie;Gan Xusheng;Shen Di;Yang Wenda;Chen Daxiong(Air Traffic Control and Navigation School,Air Force Engineering University,Xi'an 710051,China;National Key Laboratory of Air Traffic Collision Prevention,Xi'an 710051,China;PLA 95140 Troops,Huizhou 516000,China;PLA 94755 Troops,Zhangzhou 363000,China)

机构地区：[1]空军工程大学空管领航学院,陕西西安710051 [2]国家空管防相撞技术重点实验室,陕西西安710051 [3]中国人民解放军95140部队,广东惠州516000 [4]中国人民解放军94755部队,福建漳州363000

出　　处：《系统仿真学报》2025年第1期155-166,共12页Journal of System Simulation

基　　金：国家社会科学基金重点项目(21AGL030);陕西省科技计划(2022JM-412)。

摘　　要：针对战斗机在自由飞行过程中的多机冲突解脱问题,提出一种基于动态挥发因子的混沌蚁群算法。对战斗机空中多机冲突解脱问题进行数学建模,基于战斗机性能特点,分别建立了战斗机保护区模型、飞行冲突模型和解脱模型;对混沌蚁群算法进行改进,采用Logistic映射和Henon映射分别优化蚁群算法中的信息素更新公式,同时将信息素挥发因子设置动态因子,以提高不同阶段的搜索效率。设置典型的2机、4机和6机飞行冲突场景,对算法的有效性进行了仿真验证,结果表明,优化后的算法可行,算法的各项性能指标均有所提升。A chaotic ant colony algorithm based on dynamic volatility factor is proposed to solve the problem of multi-aircraft conflict resolution during free flight of fighter jets.The mathematical modelling is conducted on the conflict resolution problem of multiple fighter jets in the air.Based on the performance characteristics of fighter jets,fighter protection zone models,flight conflict models,and resolution models are established respectively.The chaotic ant colony algorithm is improved by using Logistic mapping and Henon mapping to optimize the pheromone update formula in the ant colony algorithm,and setting a dynamic factor for the pheromone volatilization factor to improve search efficiency at different stages.The typical 2-aircrafts,4-aircrafts,and 6-aircrafts flight conflict scenarios are set up to simulate and verify the effectiveness of the algorithm.The results show that the optimized algorithm is feasible,and all performance indicators of the algorithm are improved.

关 键 词：混沌算法 蚁群算法 多机飞行冲突解 混沌映射 动态因子 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]