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Pattern synthesis of linear antenna-array for high gain and low sidelobe level based on sand cat swarm optimization algorithm: Pattern synthesis of linear antenna-array for high gain…: J. Mou et al.

Authors :
Mou, Jianhui
Wang, Jian
Wang, Yangwei
Xiang, Ming
Zhang, Lihua
Source :
Journal of Supercomputing. Jan2025, Vol. 81 Issue 1, p1-21. 21p.
Publication Year :
2025

Abstract

This study presents a novel optimization method based on the sand cat swarm optimization (SCSO) algorithm for the pattern synthesis of linear antenna-array (LAA), aiming to obtain the high gain and low sidelobe level (SLL). The innovation of the proposed method consists in efficiently regulating the radiation characteristics of the LAA by optimizing the geometric and electrical parameters including the phase, amplitude, rotation and position based on the SCSO algorithm to achieve the desired radiation performances. The full-wave method of moments (MoM) is adopted to rigorously consider the mutual coupling effect among the array elements to guarantee the design accuracy. To demonstrate the feasibility and effectiveness of the SCSO algorithm, the proposed method is compared with three typical algorithms, including the Genetic Algorithm (GA), the Gray Wolf (GWO) algorithm, and the Particle Swarm Optimization (PSO). The results show that the SCSO algorithm demonstrates superior convergence capabilities while maintaining the high gain and low SLL, highlighting the potential as a robust method for the LAA. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09208542
Volume :
81
Issue :
1
Database :
Academic Search Index
Journal :
Journal of Supercomputing
Publication Type :
Academic Journal
Accession number :
181820180
Full Text :
https://doi.org/10.1007/s11227-024-06763-w