Circular antenna array synthesis with a Differential Invasive Weed Optimization algorithm

Annirudha Basak, S. Pal, Swagatam Das, A. Abraham
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引用次数: 32

Abstract

In this article we describe an optimization-based design method for non-uniform, planar, and circular antenna arrays with the objective of achieving minimum side lobe levels for a specific first null beamwidth and also a minimum size of the circumference. Central to our design is a hybridization of two prominent metaheuristics of current interest namely the Invasive Weed Optimization (IWO) and the Differential Evolution (DE). IWO is a derivative-free real parameter optimization technique that mimics the ecological behavior of colonizing weeds. Owing to its superior performance in comparison with many other existing metaheuristics, recently IWO is being used in several engineering design problems from diverse domains. For the present application, we have modified classical IWO by incorporating the difference vector based mutation schemes from the realm of DE. Three difficult instances of the circular array design problem have been presented to illustrate the effectiveness of the hybrid Differential IWO (DIWO) algorithm. The design results obtained with modified IWO have been shown to comfortably outperform the results obtained with other state-of-the-art metaheuristics like Particle Swarm Optimization (PSO), and Differential Evolution (DE) in a statistically significant fashion.
基于差分入侵杂草优化算法的圆形天线阵列合成
在本文中,我们描述了一种基于优化的非均匀、平面和圆形天线阵列的设计方法,其目标是在特定的第一零波束宽度和最小的周长尺寸下实现最小的旁瓣电平。我们设计的核心是两个突出的当前感兴趣的元启发式杂交,即入侵杂草优化(IWO)和差异进化(DE)。IWO是一种模拟杂草生态行为的无导数实参数优化技术。由于与许多其他现有的元启发式方法相比,IWO具有优越的性能,最近被用于不同领域的几个工程设计问题。对于目前的应用,我们通过加入来自DE领域的基于差分向量的突变方案来改进经典的IWO。提出了三个圆形阵列设计问题的困难实例来说明混合差分IWO (DIWO)算法的有效性。使用改进的IWO获得的设计结果已被证明在统计上显著优于使用其他最先进的元启发式方法如粒子群优化(PSO)和差分进化(DE)获得的结果。
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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