A Multi-objective approach to Subarrayed Linear Antenna Arrays Design

Abstract In this paper we present a multi-objective optimization approach to subarrayed linear antenna arrays design. We define this problem as a bi-objective one. We consider two objective functions for directivity maximization and sidelobe level minimization. Two popular Multi-Objective Evolutionary Algorithms (MOEAs), the Generalized Differential Evolution (GDE3) and the Nondominated Sorting Genetic Algorithm-II (NSGA-II), are employed in this study. GDE3 and NSGA-II are applied to the synthesis of uniform and nonuniform subarrayed linear arrays, providing an extensive set of solutions for each design case. Depending on the desired array characteristics, the designer can select the most suitable solution. The results of the proposed method are compared with those reported in the literature, indicating the advantages and applicability of the multi-objective approach