匹配优化算法在无人机群目标拦截的应用研究  

Application of Matching Optimization Algorithm in UAV Group Target Interception

作　　者：刘旭东[1] 贺金鑫[2] LIU Xudong;HE Jinxin(School of Information and Media,Jilin Economic Management Cadre College,Jilin Changchun 130012,China;School of Earth Sciences,Jilin University,Jilin Changchun 130061,China)

机构地区：[1]吉林省经济管理干部学院信息传媒学院,吉林长春130012 [2]吉林大学地球科学学院,吉林长春130061

出　　处：《机械设计与制造》2025年第4期336-343,共8页Machinery Design & Manufacture

基　　金：2020年产学合作协同育人项目—固定翼无人机的非线性飞行控制与路径跟踪控制技术研究(20A590051)。

摘　　要：针对无人机群拦截运动目标的问题,提出了一种最优匹配优化算法。该优化算法在经典的纯追踪制导律的基础上,结合Kunhn-Munkres(KM)算法和匈牙利算法。在拦截过程中采用卡尔曼滤波估计目标位置,减小目标位置观测的测量误差,引入虚拟领航无人机的概念来维持编队,并根据多旋翼无人机的飞行特点设计编队策略。通过仿真对比实验表明,采用所提出的最优制导策略,无人机群能够在保持预定编队的前提下拦截运动目标,缩短了所有无人机的平均每采样周期总飞行距离,加快了拦截过程,提高了编队完成度。Aiming at the problem of unmanned aerial vehicles intercepting moving targets,an optimal matching optimization al⁃gorithm is proposed.Based on the classical pure tracking guidance law,the optimization algorithm combines Kunhn-Munkres(KM)algorithm and Hungarian algorithm.In the interception process,Kalman filter is used to estimate the target position,re⁃duce the measurement error of target position observation,introduce the concept of virtual pilot UAV to maintain the formation,and design the formation strategy according to the flight characteristics of multi rotor UAV.The simulation results show that with the proposed optimal guidance strategy,the UAV group can intercept the moving target on the premise of maintaining the prede⁃termined formation,shorten the average total flight distance per sampling cycle of all UAV,speed up the interception process and improve the formation completion.

关 键 词：无人机 目标拦截 追踪算法 匹配优化算法 

分 类 号：TH16[机械工程—机械制造及自动化] V279.2[航空宇航科学与技术—飞行器设计]