4.2 Article

Optimal Pattern Synthesis of Thinned and Non-Uniformly Excited Concentric Circular Array Antennas using Hybrid GSA-PSO Technique

期刊

RADIOENGINEERING
卷 28, 期 2, 页码 369-385

出版社

SPOLECNOST PRO RADIOELEKTRONICKE INZENYRSTVI
DOI: 10.13164/re.2019.0369

关键词

Concentric circular antenna array; Gravitational Search Algorithm (GSA); Particle Swarm Optimization (PSO); Side Lobe Level (SLL); thinning; Gravitational Search Algorithm hybridized with Particle Swarm Optimization (GSA-PSO)

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Side Lobe Level (SLL) is considered as the most significant array pattern parameter as it helps in reducing surrounding noise and interference. As higher SLL value results in higher wastage of power in undesired direction, transmitters of wireless communication systems face serious problems. In this paper, the optimal design of seven different sets of concentric circular antenna arrays (CCAAs) of isotropic antenna has been represented with the goal of maximum reduction in SLL. Optimal pattern synthesis of the proposed arrays has been executed by optimizing the normalized current distributions of array elements having fixed inter-element spacing. In present work inter-ring spacing has been fixed at 0.5 lambda. In order to achieve low SLL in the radiation pattern of the optimized array antenna, many conventional optimization methods have been proposed in last few decades for handling complex, non-differentiable, discontinuous and highly nonlinear array factor. To deal with the problems of premature convergence (fall into local optima) feature of gravitational search algorithm (GSA) and particle swarm optimization (PSO) has been merged. In high-dimensional space, gravitational search algorithm hybridized with particle swarm optimization (GSA-PSO) is considered while preserving the fast converging property of them. Numerical results in the present text assume the pattern synthesis of thinned array and non-uniformly excited array for seven different sets of CCAA geometries. An exhaustive simulation results are presented and the radiation pattern performances are analyzed. As compared with conventional optimization techniques like GSA and PSO, hybrid GSA-PSO technique outperforms with the goal of maximum SLL suppression.

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