Multi-target Collaborative Combat Decision-Making by Improved Particle Swarm Optimizer  

作　　者：Ding Yongfei Yang Liuqing Hou Jianyong Jin Guting Zhen Ziyang 

机构地区：[1]Science and Technology on Avionics Integration Laboratory,Shanghai 200233,P.R.China [2]College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,P.R.China [3]China National Aeronautical Radio Electronics Research Institute,Shanghai 200233,P.R.China

出　　处：《Transactions of Nanjing University of Aeronautics and Astronautics》2018年第1期181-187,共7页南京航空航天大学学报（英文版）

基　　金：jointly granted by the Science and Technology on Avionics Integration Laboratory and the Aeronautical Science Foundation of China (No. 2016ZC15008)

摘　　要：A decision-making problem of missile-target assignment with a novel particle swarm optimization algorithm is proposed when it comes to a multiple target collaborative combat situation.The threat function is established to describe air combat situation.Optimization function is used to find an optimal missile-target assignment.An improved particle swarm optimization algorithm is utilized to figure out the optimization function with less parameters,which is based on the adaptive random learning approach.According to the coordinated attack tactics,there are some adjustments to the assignment.Simulation example results show that it is an effective algorithm to handle with the decision-making problem of the missile-target assignment(MTA)in air combat.A decision-making problem of missile-target assignment with a novel particle swarm optimization algorithm is proposed when it comes to a multiple target collaborative combat situation.The threat function is established to describe air combat situation.Optimization function is used to find an optimal missile-target assignment.An improved particle swarm optimization algorithm is utilized to figure out the optimization function with less parameters,which is based on the adaptive random learning approach.According to the coordinated attack tactics,there are some adjustments to the assignment.Simulation example results show that it is an effective algorithm to handle with the decision-making problem of the missile-target assignment(MTA)in air combat.

关 键 词：collaborative combat multi-target decision-making improved particle swarm optimization(IPSO) 

分 类 号：V249[航空宇航科学与技术—飞行器设计]