A Case Study for Improving Performance of Frequency Selective Surface through Union of Sub-Sets and Particle Swarm Optimization

Abstract

Frequency Selective Surfaces (FSSs) consist of a repetition of a given pattern in a periodic way; typically, a dielectric substrate supports this arrangement giving rise to a two-dimensional array. Although relatively simple in structure, designing an FSS that exhibits large bandwidth and stable response to oblique incidence is not straightforward and requires special attention and significant computational effort. To address this problem, this study presents a methodology whereby an initial configuration of the FSS pattern is subjected to an optimization method for sizing the geometrical parameters. Consequently, the initial unit cell is first broken down into subsections, specifically as a 'union of subsets', then particle swarm optimization is used to achieve optimal design parameters that further improves the overall FSS performances. To validate the proposed method, an X-band FSS is proposed and optimized in a commercial simulation environment (Microwave Studio, Dassault Systèmes). © 2022 IEEE.