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无人机群协同作战中,如何确定各无人机的航迹是整个规划问题的基础和关键,直接影响到作战效率。采用层次分解策略,首先对威胁场进行Voronoi图环境建模,然后利用改进蚁群算法,提出带有方向性引导性的信息素更新策略,减小迷失蚂蚁对算法收敛性的影响。同时,从时域和空域方面考虑多机协同问题,在满足最小时间窗基础上,最后仿真得到了航迹规划层上多无人机的协同航迹。结果表明:该算法有效地克服了早熟停滞现象,解决了求解多样性问题,并加快了算法的求解效率。
In the coordinated operation of UAVs, how to determine the trajectory of each UAV is the basis and key of the whole planning problem, which directly affects the operational efficiency. By using the hierarchical decomposition strategy, the Voronoi diagram environment of the threat field is modeled first, and then the improved pheromone algorithm is used to propose the direction-oriented pheromone updating strategy to reduce the influence of the lost ant on the convergence of the algorithm. At the same time, considering the multi-machine coordination problem in the time domain and the airspace, based on meeting the minimum time window, finally, the cooperative trajectory of multi-UAV on the trajectory planning level is obtained. The results show that this algorithm can effectively overcome the premature stagnation, solve the problem of solving diversity, and accelerate the efficiency of the algorithm.