Analysis of Circular Antenna Array Using Machine Learning Technique

This paper presents an approach to design 20, 36-elements asymmetric circular antenna array (CAA) for optimum far-field radiation pattern synthesis. By minimizing the sidelobe levels (SLLs), the far-field radiation pattern is designed to minimize the sidelobe level and first null beamwidth of CAA. For achieving the ultra-low SLLs, an optimal combination of excitation amplitude and phase is determined using a proposed machine learning technique which is Gradient Decent.

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Publication Details

Published
2025-06-05
DOI
https://doi.org/10.1109/wams64402.2025.11158890
Primary Topic
Antenna Design and Optimization
Type
article
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article

Analysis of Circular Antenna Array Using Machine Learning Technique

Durbadal Mandal, Satish Kumar, Ankush Kumar Singh, D Babu
Antenna Design and Optimization
article

Analysis of Circular Antenna Array Using Machine Learning Technique

Durbadal Mandal, Satish Kumar, Ankush Kumar Singh, D Babu
article en

Abstract

This paper presents an approach to design 20, 36-elements asymmetric circular antenna array (CAA) for optimum far-field radiation pattern synthesis. By minimizing the sidelobe levels (SLLs), the far-field radiation pattern is designed to minimize the sidelobe level and first null beamwidth of CAA. For achieving the ultra-low SLLs, an optimal combination of excitation amplitude and phase is determined using a proposed machine learning technique which is Gradient Decent.

National Institute of Technology Durgapur (IN)
Openalex Percentile: Top 66%
Antenna Design and Optimization
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