Novel Metaheuristic Optimization Algorithms for Sidelobe Suppression of Linear Antenna Array

A. Durmuş
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引用次数: 4

Abstract

In this study, the problem of sidelobe suppression in the antenna radiation patterns on which antenna designers work intensively, is discussed. For this optimization problem, analyses are carried out with the newly introduced Honey Badger Algorithm (HBA) and Chameleon Swarm Algorithm (CSA) algorithms in the literature. In addition, to test the performance of these algorithms, Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO) methods, which are well known in the literature, are also used in sidelobe suppression in antenna arrays. For the statistical comparison of these four optimization methods, thirty independent runs are made, and the results are tabulated.
线性天线阵旁瓣抑制的新型元启发式优化算法
在本研究中,讨论了天线设计人员集中工作的天线辐射方向图中的旁瓣抑制问题。针对这一优化问题,本文采用文献中新引入的Honey Badger Algorithm (HBA)和Chameleon Swarm Algorithm (CSA)算法进行了分析。此外,为了测试这些算法的性能,文献中众所周知的人工蜂群(Artificial Bee Colony, ABC)和粒子群优化(Particle Swarm Optimization, PSO)方法也被用于天线阵列的副瓣抑制。为了对这四种优化方法进行统计比较,进行了30次独立运行,并将结果制成表格。
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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