Preliminary Analysis of mmWave SAR Model and Machine Learning Approach

被引：0

作者：

Wadde, Chandra ^{[1
]}

Routhu, Gayatri ^{[1
]}

Karvande, Rajesh Shankar ^{[2
]}

Kumar, Rupesh ^{[1
]}

机构：

[1] SRM Univ, Wireless Sensing & Imaging, Amaravati, Andhra Pradesh, India

[2] DRDO, Res Ctr Imarat, Hyderabad, India

来源：

2024 IEEE SPACE, AEROSPACE AND DEFENCE CONFERENCE, SPACE 2024 | 2024年

关键词：

Machine learning; image processing; Convolutional Neural Network (CNN); mmWave FMCW radar; MATLAB; !text type='Python']Python[!/text;

D O I：

10.1109/SPACE63117.2024.10668181

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

Machine learning (ML) techniques have been ap-plied for radar applications in recent years. It is still changeling to classify images or objects accurately. This work has modeled 1600 reconstructed object shapes of four different objects like triangles, circles, squares, and rectangles using millimeter-wave (mmWave) FMCW radar principle based on the 2D SAR imaging technique, and the numerical analysis is performed in MATLAB. The Convolution Neural Network (CNN) technique is implemented to perform the objects' classification in a Python environment. The results give a good prospect for the study of ML techniques to classify mmWave FMCW radar data.

引用

页码：1148 / 1151

页数：4

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