Optimal Configuration and Performance Enhancement of Time-Modulated Circular Antenna Arrays

IF 1.5 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-07-10 DOI:10.1109/JMMCT.2025.3587386

Satish Kumar;Gopi Ram;Durbadal Mandal;Rajib Kar

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引用次数: 0

Abstract

In order to optimize the synthesis of Asymmetric Time-Modulated Circular Antenna Array (ATMCAA) and Symmetric Time-Modulated Circular Antenna Array (STMCAA), this work presents the Novel Particle Swarm Optimization Algorithm (NPSO). Inter-element spacing and uniform current excitation are maintained by regulating the switching time sequence and progressive phase delay of each element. A distinct cost function is developed for each of the two case studies. Using 20- and 36-element examples, several low side-lobe designs synthesized from ATMCAA and STMCAA are compared with traditional circular arrays. Through the manipulation of switching time sequence and progressive phase delay, the cost function is optimized to simultaneously reduce the side-lobe level (SLL) and directivity in ATMCAA and STMCAA. When it comes to antenna array synthesis, NPSO performs better than other algorithms, such as cat swarm optimization and invasive weed optimization. This study demonstrates how effective NPSO is at optimizing antenna arrays in order to improve higher communication reliability and signal quality.

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时间调制圆形天线阵列的优化配置与性能增强

为了优化非对称时调制圆形天线阵列（ATMCAA）和对称时调制圆形天线阵列（STMCAA）的合成，本文提出了一种新的粒子群优化算法（NPSO）。通过调节各元件的开关时间顺序和逐级相位延迟来保持元件间的间距和电流的均匀励磁。为这两个案例研究中的每一个开发了不同的成本函数。以20元和36元为例，比较了由ATMCAA和STMCAA合成的几种低旁瓣设计。通过控制开关时间序列和渐进相位延迟，优化了代价函数，同时降低了ATMCAA和STMCAA的旁瓣电平（SLL）和指向性。在天线阵列综合方面，NPSO的性能优于其他算法，如猫群优化和入侵杂草优化。本研究证明了NPSO在优化天线阵列以提高通信可靠性和信号质量方面的有效性。

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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来源期刊

IEEE Journal on Multiscale and Multiphysics Computational Techniques Mathematics-Mathematical Physics

CiteScore

4.30

自引率

0.00%

发文量