考虑战场环境约束的多导弹协同任务规划

Cooperative Mission Planning of Multi-Missile with Battlefield Environment Constraint

多导弹协同任务规划是一个多约束、强耦合的复杂多目标优化与决策问题,能有效提高作战效能。研究了具有不同探测距离和威胁度的禁/避飞区、威胁区等战场环境下的多导弹协同航迹规划和目标分配问题。首先建立了具有战场环境约束的Voronoi图,并结合改进的Dijkstra算法取得了代价最小的航迹;进一步采用基于视线的航迹缩短算法和航迹平滑算法对初始航迹进行动态优化处理,产生了既节省燃料又满足导弹机动性能的可飞行轨迹;最后采用基于MMKP(Multi-dimensional,Multi-choice Knapsack Problem)的协同目标分配算法实现了多导弹协同攻击多目标,并且获得了综合代价最小的多导弹协同航迹。仿真结果证明了方法的有效性。该方法具有很高的应用价值,可实际应用在巡航导弹、无人机等无人飞行器的协同控制方面。

Multi-missile cooperation was a complicated multi-objective optimization and decision-making problem with many strongly coupling constraints,and its objective was to improve the operation effectiveness of missiles.A cooperative path-planning and target allocation approach based on battlefield environment with threats and no-fly zones was developed.Firstly,a Voronoi diagram considering battlefield constrains was completed,and the improved Dijkstra＇s algorithm was selected for obtaining the minimum-cost paths.Then the initial paths were processed dynamically by using LOS based path shortening method and path smoothing algorithm,and the flyable paths that could save fuel and satisfy missile＇mobile performance were obtained.At last,taking the problem as a Multi-dimensional,Multi-choice Knapsack Problem（MMKP）,the cooperative mission of multi-missile attacking multi-target was realized,and the multi-missile cooperative paths with a minimum overall mission cost were obtained.Simulation results proved the validity of the approach.The multi-missile approach can be applied in cooperation control for a team of unmanned air vehicles such as cruise missiles etc.