一种基于蚁群智能算法的航迹优化方法

A Kind of Air Route Optimizing Method Based on Ant Colony Algorithm

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。

Air route planning is critical in the system of flight terrain avoidance. It is the basis to accomplish the low-altitude flying task. The air route planning for flight terrain avoidance is researched, classify and model the terrain sampled point by using k mean-value algorithm, and set up the feasible point space. And then the Dijkstra algorithm to make initial air route planning is used. Optimizing the air route by using the ant colony algorithm, range of the air route is cut down. Through the simulation, the feasibility and rationality of the scheme are verified.