Optimal Pattern Synthesis of Linear Antenna Array Using Grey Wolf Optimization Algorithm

Abstract

The aim of this paper is to introduce the grey wolf optimization (GWO) algorithm to the electromagnetics and antenna community. GWO is a new nature-inspired metaheuristic algorithm inspired by the social hierarchy and hunting behavior of grey wolves. It has potential to exhibit high performance in solving not only unconstrained but also constrained optimization problems. In this work, GWO has been applied to linear antenna arrays for optimal pattern synthesis in the following ways: by optimizing the antenna positions while assuming uniform excitation and by optimizing the antenna current amplitudes while assuming spacing and phase as that of uniform array. GWO is used to achieve an array pattern with minimum side lobe level (SLL) along with null placement in the specified directions. GWO is also applied for the minimization of the first side lobe nearest to the main beam (near side lobe). Various examples are presented that illustrate the application of GWO for linear array optimization and, subsequently, the results are validated by benchmarking with results obtained using other state-of-the-art nature-inspired evolutionary algorithms. The results suggest that optimization of linear antenna arrays using GWO provides considerable enhancements compared to the uniform array and the synthesis obtained from other optimization techniques.

Forecasting of Power Grid Investment in China Based on Support Vector Machine Optimized by Differential Evolution Algorithm and Grey Wolf Optimization Algorithm

“…Grey wolf optimization (GWO) algorithm is a novel heuristic swarm intelligence optimization algorithm proposed by Mirjalili et al in 2014, which has good performance in global search and convergence [40]. GWO simulates the social hierarchy and hunting behavior of the grey wolf population [41,42].…”

“…The differential evolution algorithm was proved to be the fastest evolutionary algorithm in the first international evolutionary computation competition in Nagoya, Japan, 1996. Grey wolf optimization (GWO) algorithm [40,41] is a novel algorithm for guiding the group to search the optimal value, which is inspired by wolves' hunting behavior and social hierarchy. It has obvious advantages in global search and convergence [42].…”

Optimization of Linear Antennas - A Survey

“…The hierarchy of grey wolves is as follows: [14] The leaders are male and female, called alphas (α). The second level in the hierarchy comprises the beta (β) wolves followed by delta (δ) wolves and the lowest ranking grey wolves are the omegas (ω).…”

“…Prerna Saxena in [13] used FPA in order to optimize the element spacing of antenna array. Prerna Saxena in [14] have applied GWO for optimizing both element spacing and excitation amplitudes of linear antenna arrays. Pal.…”

An Antenna Array Sidelobe Level Reduction Approach through Invasive Weed Optimization

“…Reference [4] also uses a BBO-based method to reduce the maximum SLL as well as to achieve the deep nulls. Saxena and Kothari [17] optimize the beam pattern of the LAA by using the grey wolf optimization (GWO) algorithm. Sun et al [18] adopt a strategy based on cuckoo search (CS) algorithm to suppress the maximum SLL of the CCAA.…”