Enhance micro-Doppler signatures-based human activity classification accuracy of FMCW radar using the threshold method

This study proposes a threshold method in the preprocessing stage to improve human activity classification accuracy by determining the region of meaningful information (RMI) on the spectrogram. Initially, a mask function, which is created by a certain threshold value, is applied to the input spectrogram to highlight the RMI from the micro-Doppler (m-D) signatures.