Meta‐heuristic optimization algorithms for comparative analysis of uniform and non‐uniform elliptical array antenna for enhanced gain

Abstract

SummaryIn this article, the synthesis of a non‐uniform elliptical array antenna (EAA) is presented applying three relatively new, well‐performing meta‐heuristic optimization algorithms; quantum particle swarm optimization (QPSO), symbiotic organism search (SOS), and moth fly optimization (MFO) algorithms. The design objective allows simultaneous minimization of side lobes and maximization of gain by finding the best optimal combination of angular locuses of the antennas in the array structure. The proposed technique is efficient enough to resolve the underlying multi‐objective problems at two principle planes of radiation and adaptable enough to the effective implementation of additional design constraints which make this design suitable for practical high‐frequency applications as well as long‐distance communication. The iterative accomplishment of the three algorithms is compared depending on the radiation parameters as well as statistical parameters. The outcomes are validated by performing a t test on the obtained data sets.