The extraction of micro-Doppler features from human motions

This study aims to experimentally investigate the feasibility of discriminating human motions with the help of micro-Doppler features by using radar. In the first phase of the work, the synthetic data is generated through the human walking simulator by V. Chen and different time-frequency transformations are applied on the data. In the following phase, several field experiments are conducted and the experimental data for running, crawling, creeping and walking with the aspect angles of 0°, 30°, 60° are collected and spectrograms are obtained. Lastly, six features, which are torso frequency, bandwidth of the signal, offset of the signal, bandwidth without micro-Dopplers, the standard deviation of the signal strength, the period of the arms or legs motions are extracted from the spectrograms and the efficiencies of the features in motion classification are compared.