基于改进粒子群算法的协同多目标攻击空战决策  

Air Combat Decision-making for Cooperative Multiple Target Attack Based on Improved Particle Swarm Algorithm

作　　者：郭辉[1] 徐浩军[2] 谷向东[2] 刘殿玉[2] 

机构地区：[1]空军航空大学,长春130022 [2]空军工程大学工程学院,西安710038

出　　处：《火力与指挥控制》2011年第6期49-51,55,共4页Fire Control & Command Control

基　　金：国家自然科学基金资助项目(70671106)

摘　　要：超视距空战和协同多目标攻击是空战的发展趋势,协同多目标攻击中的关键问题是空战决策。建立了协同多目标攻击空战决策的多目标优化数学模型,提出了一种改进的粒子群优化算法,并将其应用于空战决策。基本的粒子群算法是一个有效的求解连续优化问题的方法,结合遗传算法的思想,提出了直接对粒子进行交叉和变异操作来完成粒子更新的方法。仿真结果表明,所提出的改进粒子群算法是一种求解协同多目标攻击空战决策问题的有效算法。Beyond-Visual-Range air combat and cooperative multiple target attack are the trend ot air combat, the key problem of cooperative multiple target attack is air combat decision-making. The model of multi-objective optimization problem for air combat decision-making was established, an improved particle swarm algorithm was put forward to solve air combat decision-making. The basic particle swarm algorithm is an effective method to solve the continuous optimization problem, the method of operating the particle directly by crossing and mutating combining the ideal of the genetic algorithm to update particle was proposed.. The simulation results showed that the proposed algorithm was an effective algorithm to deal with the air combat decision-making problem.

关 键 词：多目标攻击 空战决策 多目标优化 粒子群算法 

分 类 号：V247[航空宇航科学与技术—飞行器设计]