A new method of radar antenna scanning mode recognition using LightGBM

In order to recognize the radar antenna scanning mode automatically and improve the recognition accuracy, the feature extraction and recognition methods of electronic scanning and mechanical scanning are studied respectively, and a new electronic warfare antenna scanning recognition algorithm is proposed. The algorithm mainly includes scan period estimation, pre-processing (normalization, resampling, averaging), feature extraction and classification using LightGBM algorithm. The distinction between electronic scanning and mechanical scanning is realized based on the characteristic parameters of the maximum main-lobe pulse train, and then the automatic recognition of six mechanical scanning modes is realized based on the characteristic parameters of the scanning period pulse train of a single antenna. The simulation results show that the proposed method can distinguish one-dimensional electrical scanning, two-dimensional electrical scanning and mechanical scanning, and can identify the radar antenna scanning mode more accurately than the traditional decision tree (DT) and support vector machine (SVM).

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Publication Details

Published
2025-03-31
DOI
https://doi.org/10.1117/12.3061659
Primary Topic
Advanced SAR Imaging Techniques
Type
article
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article

A new method of radar antenna scanning mode recognition using LightGBM

Yongle Li, Peng Xu, Weihua Li, Peng Deng et al.
Advanced SAR Imaging Techniques
article

A new method of radar antenna scanning mode recognition using LightGBM

Yongle Li, Peng Xu, Weihua Li, Peng Deng, Bo Yang
article en

Abstract

In order to recognize the radar antenna scanning mode automatically and improve the recognition accuracy, the feature extraction and recognition methods of electronic scanning and mechanical scanning are studied respectively, and a new electronic warfare antenna scanning recognition algorithm is proposed. The algorithm mainly includes scan period estimation, pre-processing (normalization, resampling, averaging), feature extraction and classification using LightGBM algorithm. The distinction between electronic scanning and mechanical scanning is realized based on the characteristic parameters of the maximum main-lobe pulse train, and then the automatic recognition of six mechanical scanning modes is realized based on the characteristic parameters of the scanning period pulse train of a single antenna. The simulation results show that the proposed method can distinguish one-dimensional electrical scanning, two-dimensional electrical scanning and mechanical scanning, and can identify the radar antenna scanning mode more accurately than the traditional decision tree (DT) and support vector machine (SVM).

Chongqing University of Posts and Telecommunications (CN), Chongqing University (CN), PLA 306 Hospital (CN)
Affordable and clean energy
Openalex Percentile: Top 92%
Advanced SAR Imaging Techniques
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