粒子群算法在激光武器反无人机火力分配中的应用

Application of Particle Swarm Optimization in Anti‑UAV Fire Allocation of Laser Weapon

针对激光武器反无人机作战的特点,研究了粒子群算法在火力分配中的应用策略。根据激光武器对抗无人机的作战过程,从作战资源约束、时空关系和引导概率等方面分析了激光武器对无人机的拦截条件,结合毁伤效率和尽早拦截原则建立了火力分配模型。为解决多目标场景下的组合爆炸问题,提出了改进的粒子群寻优算法,基于武器拦截可行域对分配问题进行了降维处理,引入正、负反馈学习机制和多样性修正策略,以权衡优化结果与计算时间之间的矛盾。仿真试验表明,该算法能够快速处理多目标分配问题,且具有良好的稳定性。

Aimed at the characteristics of laser weapon anti-UAV operation,the application strategy of particle swarm optimization algorithm in fire allocation is studied.According to the combat process of laser weapon against UAV,the interception conditions of laser weapon against UAV are analyzed from the aspects of combat resource constraint,space-time relationship and direct probability,and the fire allocation model is established based on damage efficiency and time to interception.In order to solve the combined explosion problem in multi-target scenarios,an improved particle swarm optimiza⁃tion algorithm is proposed to reduce the dimension of the allocation problem based on the feasible re⁃gion or weapon interception,and positive and negative feedback learning mechanism and diversity cor⁃rection strategy are introduced.Simulation results show that this algorithm can deal with target alloca⁃tion problem quickly,and has good stability.