现代雷达2026，Vol.48Issue(3)：26-36,11.DOI:10.16592/j.cnki.1004-7859.2025008
面向目标无源定位的无人机群路径优化研究
A Study on Path Optimization of Unmanned Aerial Vehicle Swarm for Target Passive Positioning
摘要
Abstract
The target passive positioning accuracy of unmanned aerial vehicle swarm is closely related to the aerial topology structure of the unmanned aerial vehicle swarm.By optimizing the travel path of unmanned aerial vehicle swarm,the target passive positio-ning accuracy can be effectively improved.Meanwhile,when there are a large number of unmanned aerial vehicle swarm sites,the efficiency of path optimization can be effectively improved and the timeliness of unmanned aerial vehicle swarm path optimization can be enhanced by intelligent algorithms.Based on that,a path optimization algorithm for unmanned aerial vehicle swarm is pro-posed in this paper,which is based on the Cramér-Rao low bound(CRLB).The particle swarm optimization(PSO)algorithm is also employed to accelerate the path optimization process of the unmanned aerial vehicle swarm,ultimately achieving fast and effi-cient optimization of unmanned aerial vehicle swarm path for target passive positioning,and improving the accuracy of target passive positioning.First,a passive target positioning signal model is established in this paper,and the time-difference-of-arrival positio-ning algorithm is used for target passive positioning.Subsequently,a path optimization algorithm for unmanned aerial vehicle swarm based on CRLB is proposed.By minimizing the CRLB of target positioning at each moment,the next moment's position of the unmanned aerial vehicle swarm site is optimized to improve the accuracy of target passive positioning.Then,through the PSO intelligent algorithm,the process of optimizing the position of unmanned aerial vehicle nodes is accelerated,while the speed of path optimization is improved and the timeliness of optimization algorithm is enhanced.Finally,the correctness and effectiveness of the proposed algorithm are verified through simulations.关键词
无人机群目标无源定位/到达时间差/路径优化/克拉美罗下界/粒子群优化算法Key words
target passive positioning of unmanned aerial vehicle swarm/time-difference-of-arrival(TDOA)/path optimization/Cramér-Rao lower bound(CRLB)/particle swarm optimization(PSO)algorithm分类
航空航天引用本文复制引用
陈亮,李雪婷,何振清,张玥,沙晓鹏..面向目标无源定位的无人机群路径优化研究[J].现代雷达,2026,48(3):26-36,11.基金项目
国家自然科学基金资助项目(50704012) （50704012）
辽宁省博士启动基金资助项目(20061017) （20061017）
