基于战争策略优化的天线阵列图案合成和微带贴片天线优化方法

IF 2.2 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Renjing Gao, Wei Tong, Mingyue Zhang, Qi Wang
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引用次数: 0

摘要

本文首先介绍了战争策略优化(WSO)算法在天线阵列图案合成和微带贴片天线尺寸优化中的应用。作为一种受自然界启发的新型进化算法,WSO 算法在解决包括非线性和非凸性在内的复杂问题时具有全局优化能力,因此在上述两个典型的多变量非线性问题中将发挥其潜在优势。在解决图案合成问题时,选取了不同元素的线性天线阵列的减少侧叶合成和空心控制作为数值案例,WSO 算法分别通过只优化振幅和只优化相位实现了所需的主波束宽度和空心深度。在微带贴片天线的尺寸优化方面,WSO 算法通过优化矩形贴片天线的宽度和长度,在 3.1G Hz 频率下实现了 - 80 dB 的最小反射系数(S11)。此外,与蚱蜢优化算法、灰狼优化算法和入侵杂草优化算法相比,WSO 算法在解决上述两类优化问题时表现出更高的计算精度和更快的收敛速度。因此,WSO 算法可广泛应用于电磁结构设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

War strategy optimization-based methods for pattern synthesis of antenna arrays and optimization of microstrip patch antenna

War strategy optimization-based methods for pattern synthesis of antenna arrays and optimization of microstrip patch antenna

War strategy optimization-based methods for pattern synthesis of antenna arrays and optimization of microstrip patch antenna

This paper first presents an application of the war strategy optimization (WSO) algorithm in pattern synthesis of antenna arrays and dimensions optimization of microstrip patch antenna. As a new type of evolutionary algorithm inspired by nature, the WSO algorithm has global optimization ability in solving complex problem including nonlinearity and nonconvexity; therefore, it will exhibit the potential advantages in the above two typical multivariate nonlinear problems. For solving pattern synthesis problem, the sidelobe reduction synthesis and null controlling of linear antenna arrays with different element are selected as numerical cases, and the WSO algorithm achieves the desired main beams width and null depth by optimizing the amplitude-only and the phase-only, respectively. For dimensions optimization of microstrip patch antenna, the WSO algorithm realizes the minimized reflection coefficient (S11) of − 80 dB at 3.1G Hz by optimizing the width and length of rectangle patch antenna. Moreover, compared with the Grasshopper optimization algorithm, the gray wolf optimization algorithm, and the invasive weed optimization algorithm, the WSO algorithm shows higher computational accuracy and faster convergence speed for solving the above two types of optimization problem. Therefore, the WSO algorithm can be widely used to in electromagnetic structure design.

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来源期刊
Journal of Computational Electronics
Journal of Computational Electronics ENGINEERING, ELECTRICAL & ELECTRONIC-PHYSICS, APPLIED
CiteScore
4.50
自引率
4.80%
发文量
142
审稿时长
>12 weeks
期刊介绍: he Journal of Computational Electronics brings together research on all aspects of modeling and simulation of modern electronics. This includes optical, electronic, mechanical, and quantum mechanical aspects, as well as research on the underlying mathematical algorithms and computational details. The related areas of energy conversion/storage and of molecular and biological systems, in which the thrust is on the charge transport, electronic, mechanical, and optical properties, are also covered. In particular, we encourage manuscripts dealing with device simulation; with optical and optoelectronic systems and photonics; with energy storage (e.g. batteries, fuel cells) and harvesting (e.g. photovoltaic), with simulation of circuits, VLSI layout, logic and architecture (based on, for example, CMOS devices, quantum-cellular automata, QBITs, or single-electron transistors); with electromagnetic simulations (such as microwave electronics and components); or with molecular and biological systems. However, in all these cases, the submitted manuscripts should explicitly address the electronic properties of the relevant systems, materials, or devices and/or present novel contributions to the physical models, computational strategies, or numerical algorithms.
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