A comparative study of optimization algorithms for correction of radar system error

Abstract

The most important feature of radar on missile is target tracking. However, due to the radar's type of belt drive, there is a vibration resistance problem that brings too large radar system error in vibration condition between arc tooth structure. The purpose of this paper is to achieve the reduction of radar system error by using intelligent algorithms to adjust parameters of radar control system and looking for the optimum combination of parameters . In this study, based on the existing missile's radar control system model, we set up six performance indicators to evaluate radar system error. Therafter, the traditional Genetic Algorithm(GA), the Improved Genetic Algorithms(IGA), the Particle Swarm Optimization(PSO), the Particle Swarm Optimization -Improved Genetic Algorithm (PSO-IGA) were used for making the performance function minimum. The results show that it can effectively reduce radar system error by adjusting the parameters, and PSO-IGA overwhelms the others in terms of the quality of solutions and convergence rate.

Inversion correction method based on the mapping function approach for correcting troposphere refraction error

“…Correction methods for tropospheric refraction error mainly include the ray tracing method based on the Snell method, the model modification method, and new approaches [4,5]. The ray tracing method is strictly derived from the ray equation which can accurately describe the radio propagation state when the atmospheric refractive index of the radio wave propagation path is known, and the method is acknowledged to have the best accuracy [6].…”