基于 QPSO 的模糊策略博弈的多无人机空战策略

针对无人机作战指挥系统中多无人机空战博弈策略的问题,提出一种采用量子粒子群算法(quantum particle swam optimization,QPSO)在模糊策略下博弈的纳什均衡求解方法.通过对无人机空战态势信息的分析,建立敌我双方多无人机动空战的作战收益函数,根据给出的敌我双方无人机纯策略集中的模糊子集,构建基于模糊策略下的敌我双方无人机博弈支付矩阵,进而求得作战双方获得最优选择策略.仿真验证结果表明,该方法可行、有效.

Multi UAV Air Combat Strategy Based on QPSO Fuzzy Strategy Gam

Aiming at the problem of multi UAV air combat game strategy in UAV combat command system, a Nash equilibrium solution based on quantum particle swarm optimization (QPSO) under fuzzy strategy is proposed. Through the analysis of UAV combat situation information, establish multiple UAV air combat operational revenue function of both sides, according to the UAV pure strategy centralized fuzzy subset of both sides, build UAV game payoff matrix of both sides based on fuzzy strategy, then obtain the optimal selection strategy of both side. The simulation results show that the the method is offective and feasible.