应用人工免疫算法快速规划3DTF/TA^2航线

Quickly Planning TF/TA^2 Trajectory by Artificial Immune Algorithm

针对复杂环境下单(双)机TF/TA2飞行路径规划问题,提出了满足飞机可飞性和可操作性的人工免疫算法飞行航线规划方法;设计了综合3D威胁信息的惩罚函数(亲和力函数);构建了包含动态、静态威胁及不可飞区域的综合威胁模型。据此,设计了不同威胁度环境下的单、双飞行航线,并将人工免疫算法规划的航线与遗传算法进行比较。结果表明,在简单威胁环境下,遗传算法规划时间短、路径较长;在复杂环境下,遗传算法的单机规划失败率极高(大于95%),双机规划失败。人工免疫算法能够为单(双)机规划出一条最优及多条待选飞行航线。

Flight path planning by artificial immune algorithm approach met the requirements of aircraft’s flyability and operation is proposed for the problem of single and double TF/TA2 flight path planning. Punishment function (affinity function)with comprehensive 3D threat information is designed.A comprehen‐sive threat model is formed including dynamic and static threats and no‐fly‐zone.Accordingly,single and dual flight paths are planned by AIA,which have been compared with the paths by GA.The results show that,GA’s planned a quick and longer path compared under simple threat environment;in complex environments,GA has high failure rate (greater than 95%)for single aircraft,but it is failed for double aircrafts.For the single and double aircrafts,AIA can provides one optimal and more candidate optimal fl ight paths.