Preliminary Analysis of mmWave SAR Model and Machine Learning Approach

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.