Improved Particle Swarm Optimization Algorithm and its Application in Coordinated Air Combat Missile-Target Assignment

Abstract

Based on the analysis of the basic particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to solve the problem with missile-target assignment in coordinated air combat (MTACAC). There were three improvements: 1. Adaptive adjustment of inertia weight; 2. Amelioration of particle velocity and position; 3. Better optimization strategy. Based on the principles of coordinated air combat efficiency and operational research, a missile-target assignment mathematical model was established. The IPSO algorithm was applied to seek the optimal missile assignment scheme for multi-target coordinated air-to-air combat. The simulation result indicated that the model of MTACAC was practical and feasible, and the IPSO algorithm was fast, simple, and more effective in finding out the global optimum assignment, when compared with the basic PSO algorithm and the genetic algorithm (GA).