航路规划是飞机地形回避系统的一个关键环节,是完成低空飞行任务的基础。针对飞机地形回避过程的航路规划技术进行研究,利用k均值算法对地形采样点进行聚类,建立地形障碍空间模型。运用狄克斯特拉算法进行初始航迹规划,然后利用蚁群智能算法对航迹进行优化,缩短整个航线的航程。通过仿真验证了方案的可行性和合理性。 Route planning is a key aspect of aircraft avoidance system and is the basis for completing low-altitude missions. Aiming at the route planning technology of aircraft avoidance process, the k-means algorithm is used to cluster the topographic sampling points, and a terrain obstacle spatial model is established. Using Dikstra algorithm for initial track planning, and then using ant colony intelligent algorithm to optimize the track, shortening the voyage of the entire route. The feasibility and rationality of the scheme are verified through simulation.