Pattern synthesis of linear antenna array using chaos game optimization algorithm

Purpose This study/paper aims to introduces a fast and efficient stochastic chaos game optimization (CGO) algorithm for pattern synthesis of linear antenna array (LAA). Design/methodology/approach CGO algorithm is used to determine the optimal current amplitude and the interelement distance between the array elements of an LAA. Eleven design examples are simulated to explore the ability of CGO algorithm in minimizing peak and close-in side lobe levels, null placement and side lobe power reduction under the constraint of specified beamwidth. Findings The simulation results suggest that CGO algorithm outperforms other nature-inspired metaheuristic optimization algorithms. The fast convergence nature of CGO algorithm for discovering the optimal amplitude and position shows its usefulness for real-time applications. Originality/value CGO algorithm is first time explored for pattern synthesis of LAA. To analyze its effectiveness, two design examples are simulated in electromagnetic (EM) simulator and the result shows that MATLAB and EM simulator findings are really closely aligned. The results are also validated by the Wilcoxon and Friedman statistical test.