多无人机协同侦察时间资源分配优化

利用多无人机协同执行侦察任务，可以有效提高侦查的准确性。不同的侦察任务目标对象，重要程度往往不同，其任务价值也就存在差异，因此需要对协同侦察的无人机资源进行合理任务分配，提高协同侦察效益。本文重点考虑对无人机侦察时间资源分配的问题。首先，构建了一种自主协同资源分配机制，并以被辅助无人机为领导者，辅助无人机为跟随者，建立了斯坦伯格博弈模型。然后通过下层博弈均衡求解和上层博弈均衡求解，推导了辅助无人机最佳协助时间的闭合表达式，并得出所构建斯坦伯格博弈模型的纳什均衡解。最后对所提模型和方法进行了仿真验证，仿真结果表明，所提方法使得辅助无人机的时间资源得到充分利用，协同侦察的效用得到有效提升。

Multiple UAVs collaborative reconnaissance time resource scheduling optimization

Using multiple UAVs to cooperate in reconnaissance missions can effectively improve the accuracy of reconnaissance. The importance of different reconnaissance mission targets is often different, and their mission value is also different. Therefore, it is necessary to reasonably allocate the UAV resources for cooperative reconnaissance and improve the efficiency of cooperative reconnaissance. This paper focuses on the allocation of UAV reconnaissance time resources. Firstly, an autonomous collaborative resource allocation mechanism is constructed. Taking the assisted UAV as the leader and the auxiliary UAV as the follower, the Stackelberg game model is established. Then, by solving the lower level game equilibrium and the upper level game equilibrium, the closed expression of the optimal assistance time of the auxiliary UAV is deduced. The Nash equilibrium solution of the Stackelberg game model is obtained. Finally, the proposed model and method are verified by simulation. The simulation results show that the proposed method makes full use of the time resources of auxiliary UAV. The effectiveness of cooperative reconnaissance has been effectively improved.