Journal of Systems Engineering and Electronics

• 系统工程 • 上一篇    下一篇

基于混合算法的空战机动决策

张涛1,2,张雷1,周中良1,王琳3   

  1. 1. 空军工程大学航空航天工程学院,陕西 西安 710038;
    2. 中国人民解放军94831 部队,浙江 衢州 324001;
    3. 总参陆航研究所, 北京 101121
  • 收稿日期:2012-05-07 修回日期:2012-12-30 出版日期:2013-07-22 发布日期:2013-04-17

Decision-making for air combat maneuvering based on hybrid algorithm

ZHANG Tao1,2,YU Lei1,ZHOU Zhong-liang1,WANG Lin3   

  1. 1. College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi’an 710038,
    China; 2. Unit 94831 of the PLA, Quzhou 324001, China; 3.Army Aviation Institute, Beijing 101121, China
  • Received:2012-05-07 Revised:2012-12-30 Online:2013-07-22 Published:2013-04-17

摘要:

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,结合滚动时域思想对战斗机空战机动决策进行研究。首先借鉴人工势场法构建战斗机空战人工势场,重点分析空战人工势场函数和变权重函数的构建;提出一种基于滚动时域控制-人工势场启发粒子群混合算法的战斗机空战机动决策方法;最后进行仿真验证,仿真结果表明该方法可以有效避免人工势场法局部极小值问题,改善粒子群算法的全局搜索能力,从而在一定程度上提高了战斗机在空战过程中的人工势场值,使战斗机在空战中占据有利态势。

Abstract:

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 in order to resolve the complicated problem of air combat decision-making. Adopting artificial potential field (APF), the air combat APF is built. Mainly discusses the APF function and weight function. 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 local minima of APF, and meliorate the global optimization ability of PSO. The value of artificial potential field can be improved, and the fighter can hold the advantaged situation.