Optimal sidelobe reduction of symmetric linear antenna array using Genetic Algorithm

Sudipta Das, Somen Bhattacherjee, D. Mandal, A. Bhattacharjee
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引用次数: 20

Abstract

In this paper synthesis of symmetric linear antenna arrays is described using Genetic Algorithm (GA). Genetic Algorithm has many advantages over other conventional optimization techniques. Real coded GA (RGA) is a high performance evolutionary optimization algorithm. It is used in this paper to find optimum inter-element spacing and excitation coefficients for the symmetric linear antenna array in order to minimize the maximum relative sidelobe level (SLL) in the radiation pattern of the array for minimum possible First Null Beamwidth (BWFN) increment.
基于遗传算法的对称线性天线阵旁瓣优化抑制
本文介绍了用遗传算法合成对称线性天线阵列的方法。遗传算法与其他传统的优化技术相比具有许多优点。实编码遗传算法(RGA)是一种高性能的进化优化算法。为了使天线阵的辐射方向图中最大相对旁瓣电平(SLL)最小,并使首零波束宽度(BWFN)增量最小,本文用该方法求出了对称线性天线阵的最佳单元间距和激励系数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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