基于混合算法的空战机动决策

Decision-making for air combat maneuvering based on hybrid algorithm

针对现代战斗机空战机动决策的复杂性,以红蓝双机一对一空战为背景,结合滚动时域控制(receding ho-rizon control,RHC)思想对战斗机空战机动决策进行研究。首先借鉴人工势场(artificial potential field,APF)法构建战斗机空战人工势场,重点分析空战APF函数和变权重函数的构建;提出一种基于RHC-APF启发粒子群算法(particleswarm optimization,PSO)的战斗机空战机动决策方法。仿真结果表明,该方法可以有效避免APF法局部极小值问题,改善PSO的全局搜索能力,从而在一定程度上提高了战斗机在空战过程中的APF值,使战斗机在空战中占据有利态势。

Considering an air combat scenario involving two opposed fighters,a decision-making model for air combat maneuvering based on receding horizon control（RHC） is built to resolve the complicated problem of air combat decision-making.Adopting the artificial potential field（APF）,the air combat APF is built.Construction of the APF function and the weight function is mainly analyzed.A method of decision-making for air combat maneuvering based on APF RHC and particle swarm optimization（PSO） is proposed.Simulation results show that the algorithm can avoid the pitfall in the local minimum of APF,and meliorate the global optimization ability of PSO,thus improving the value of the artificial potential field and making the advantaged situation of the fighter.