Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays

Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays

Abstract This paper introduces a versatile and efficient design methodology for optimizing wide-angle impedance matching (WAIM) configurations, enhancing the scanning range of arbitrary antenna arrays. The three-layered structure is modeled using the generalized scattering matrices (GSMs) of the lay...

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Bibliographic Details
Main Authors: Sina Hasibi Taheri, Javad Mohammadpour, Ali Lalbakhsh, Slawomir Koziel, Stanislaw Szczepanski
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Wide-angle impedance matching (WAIM)
Machine learning (ML)
Decision tree (DT) models
Generalized scattering matrix (GSM)
Online Access:https://doi.org/10.1038/s41598-025-00310-0
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