提出了一种在雷达和复杂地形环境下应用并行遗传算法进行多无人机三维航迹规划的方法。将K-均值聚类算法与多种群协同进化的方法结合起来,采用主从式并行进化的方案,提高了收敛速度且便于分布式处理。各子种群采用自适应的进化方法,在保持多样性的同时,保证了算法的收敛性。在根据数字地图建立无人机安全飞行曲面的基础上进行地形跟随和无人机间防撞设计。仿真结果表明,该方法能一次性快速得到各无人机的低空突防三维航迹。 A method of multi-UAV 3D trajectory planning using parallel genetic algorithm in radar and complex terrain environment is proposed. By combining K-means clustering algorithm and multi-species co-evolutionary method, the master-slave parallel evolutionary scheme is used to improve the convergence speed and facilitate the distributed processing. Each subpopulation adopts an adaptive evolutionary method, which ensures the convergence of the algorithm while maintaining diversity. Based on the digital map to establish UAV flight surface safety based on terrain following and unmanned aircraft collision design. The simulation results show that this method can get the three-dimensional low-altitude penetration trajectory of each UAV rapidly at one time.