基于作战效能的无人机航路规划研究

Combat Effectiveness Based Path Planning for Unmanned Air Vehicles

综合考虑目标分配与航路规划全过程,提出一种基于作战效能的无人机航路规划方法。在航路规划层利用变长染色体遗传算法规划无人机的初始航路,在协同规划层则以作战效能为指标,运用遗传粒子群优化算法进行任务优化分配,最终得到一个备选航路集。然后,利用协同算法可在备选航路集中找到满足要求的任务航路。该方法不仅能够规划出单机或多机协同全局航路,而且还可根据威胁环境或目标变化适时修正航路,并始终保证较高攻击效能。

Considering both the target allocation and the whole path planning process, a path planning scheme for Unmanned Air Vehicles （UAV） is put forward based on combat effectiveness. In path planning layer, variable-length chromosomes genetic algorithm is used to choose the initial path. In cooperative planning layer, the combat effectiveness is taken as the index and genetic particle swarm optimization algorithm is used in task allocation for obtaining an optional path set. Then, cooperative algorithm is used in the path set for finding the path satisfying all the requirements. Results of simulation demonstrate that this method can be used for single aircraft and multi-aircraft path planning, and can modify the path according to the changing of the threat and target while keeping high attacking efficiency.