多无人机动态侦察资源分配问题研究

On Dynamic Reconnaissance Resource Allocation for Multiple UAVs

为提高多无人机动态侦察分配效率,更好地满足现代战争对多无人机动态侦察实时性的要求,建立了多无人机动态侦察资源分配模型。该模型将动态任务分配问题转化为多阶段静态分配问题,利用状态更新方法对各阶段静态分配问题的初始状态进行更新,从而提升整体分配效率。采用改进的人工蜂群算法对该模型进行求解,在选择蜜源阶段采用双向进化以增加种群的多样性,提高了算法的寻优能力。仿真结果表明,动态侦察资源分配模型相较于传统的静态分配模型具有侦察效率高、续航能力强的优势,且更适用于大规模无人机集群作战情况。

In order to improve the allocation efficiency of multi-UAV dynamic reconnaissance,and to better meet the real-time requirements of modern warfare for multi-UAV dynamic reconnaissance,a model for multi-UAV dynamic reconnaissance resource allocation of multiple UAVs is established.The model transforms the dynamic task allocation problem into a multi-stage static allocation problem,and updates the initial state of the static allocation problem of each stage by using the status updating method,so as to improve the overall allocation efficiency.The improved artificial bee colony algorithm is used to solve the model,and the bidirectional evolution is used to increase the diversity of the population at the stage of selecting the honey source,which improves the optimization ability of the algorithm.The simulation results show that the dynamic reconnaissance resource allocation model has the advantages of high reconnaissance efficiency and strong endurance compared with the traditional static allocation model,and is more suitable for large-scale UAV cluster operations.