A Comparative study on Linear Array Antenna pattern synthesis using Evolutionary Algorithms

Abstract

Antenna array is defined as a collection of multiple radiating elements (antennas) which are placed in space in uniform or nonuniform manner to get a directional radiation pattern that a single antenna generally not adequate to achieve it. In antenna array pattern side lobe level and deep nulls are major problems which cause wastage of energy. This paper presents a brief survey on previous work on optimization of the linear antenna array to achieve a radiation pattern with maximum side lobe level (SLL) reduction along with control null placement in the specified directions. To get superior ability from antenna array it is requisite to modify or synthesize its geometric configurations (as linear, circular, and rectangular etc) or its electrical parameters such as excitation amplitude, phase or distance between array elements. Modern communication system demands compact array designs with high directivity and low side lobe levels. Aimed at this problem several optimization evolutionary algorithms are presented and compared in this paper, are genetic algorithm, ant colony algorithm (ACO), modified invasive weeds optimization algorithm (MIWO), Ant Lion Optimization (ACO), Gravitational Search Algorithm (GSA) and so on.