Nondominated sorting genetic algorithm-II based sidelobe suppression of concentric regular hexagonal array of antennas

Abstract

Research in the evolutionary optimization algorithm (EA) has turned its focus towards solving real life and complex multi-objective problems (MOP). Objective of this work is to obtain good quality design parameters for uniformly excited concentric hexagonal array to achieve low sidelobe pencil beam radiation pattern and high directivity. The optimizing variables are the inter-ring gaps and inter-element gaps in each ring. The objective function vector comprises of three pattern parameters relative peak sidelobe level, peak directivity and the population of the array. Widely accepted multi-objective evolutionary algorithm, namely, Elitist Non-dominated Sorting based Genetic Algorithm (NSGA II) is utilized to achieve these solutions. Optimized design parameters are found better than un-optimized design parameters in every aspect.