Air Defense Position Calibration Process Based on Improved Particle Swarm Optimization

Abstract

In order to improve the efficiency of calibration, aiming at the shortcomings of traditional relative calibration method of a certain air defense weapon system position, an optimization method based on intelligent algorithm for the relative calibration process of vehicle in a position is proposed. In this paper, the basic process of vehicle calibration is briefly introduced. The mathematical model of calibration process is established to optimize the total calibration time. The method for solving the calibration process using discrete binary particle swarm optimization is given. Through a simulation example of a vehicle calibration problem, after comparing the optimization results of discrete binary particle swarm optimization and genetic algorithm, it shows that discrete binary particle swarm has better application value in this problem. The research shows that the discrete binary particle swarm can effectively improve the calibration efficiency.