Planar array sparse distribution based on T-2GWO algorithm

Abstract

This paper introduces an approach termed T-2GWO (Tent chaos-dual channel Grey Wolf Optimization) algorithm designed for achieving sparse distribution within constrained position ranges for planar arrays. The initial population is generated by using the Tent Chaos algorithm, modeling individual coordinate positions within the population as a two-channel matrix. Subsequently, the Grey Wolf Algorithm is employed for optimization purposes. The algorithm has verified its effectiveness under the assumption of uniform excitation and can obtain the minimum peak side lobe level, reaching peak side lobe levels of -25.78 dB and - 26.15 dB in the azimuth and pitch directions. Compared with the genetic algorithm, the reduction is 3.53 dB and 10.32 dB respectively. At the same time, better main beam radiation can be obtained.