Circular Antenna Array Design by Using Evolutionary Search Algorithms

Abstract

Abstract-Evolutionary Search Algorithms (EA) have been intensively used in solving numerical optimization problems. Since design of antenna arrays is a numerical optimization problem, EAs have been intensively used in solving antenna arrays design problems. Although EAs are widely used in antenna array design problems, a performance comparison study of the intensively used EAs for circular antenna array design problem has been scarcely studied. In this paper, 3 different circular antenna array design problems have been solved by using 15 different evolutionary search algorithms (i.e., ABC, ACS, BSA, CK, CLPSO, CMAES, DE, E2-DSA, EPSDE, GSA, JADE, JDE, PSO, SADE, S-DSA). The objective function designed for solution of the relevant circular antenna array design problems ensures minimization of side lobe levels, acquisition of maximum directivity, and null control of the non-uniform, planar circular antenna array. Obtained statistical analysis results show that S-DSA solves the relevant circular antenna array design problems statistically better than the other evolutionary algorithms used in this paper.

Linear Array Pattern Synthesis Using An Improved Multiobjective Genetic Algorithm

“…In many MOPs, many or even infinite Pareto optimal vectors are distributed in the complete PF. Nevertheless, many multiobjective optimization algorithms are to find a manageable number of Pareto optimal vectors that are evenly distributed along the PF and, thus, are good representatives of the entire PF [1][2][3][4][5][6][7][8][9][10], [24]. Found in the literature, the goal for distributing individuals is that, along with convergence to the Pareto optimal set.…”

“…Evolutionary multiobjective optimization methods, such as NSGA-II, differential evolution multiobjective (DEMO), strength-Pareto evolution algorithm (SPEA-2), and multiobjective particle swarm optimization (MOPSO), are provided for the synthesis problem of linear antenna arrays and concentric rings antenna arrays with the objectives of main beam width and SLL [1], [4][5][6][7]. NSGA-II [10] is a popular and efficient multiobjective genetic algorithm, which has been used in several engineering design problems [11][12][13][14], [30].…”

“…Multiobjective optimization for array pattern synthesis has been an academic issue [1][2][3][4][5][6][7][8][9][10]. Thinned arrays have been an object of intense research due to several advantages associated with their lower cost, weight, power, and complexity compared with the fully filled arrays.…”

A Fourier Phase Mode Approach for Chebyshev Pattern Synthesis in Circular Antenna Array

“…The computation and synthesis of current distributions for Dolph-Chebyshev patterns for linear arrays were further developed by others [11][12][13]. The synthesis of a circular array with isotropic elements are documented in [14,15,[23][24][25][26]. Some special cases of directive elements were discussed in [16,17].…”

Elliptical Antenna Array Synthesis Using Backtracking Search Optimisation Algorithm

“…It was concluded that, on the whole, BSA outperformed the compared algorithms. BSA was used for circular antenna array design 12 . BSA was used to synthesis concentric circular antenna arrays and linear antenna arrays 13,14 .…”