Radar micro-Doppler based human activity classification for indoor and outdoor environments

This paper presents the results of our experimental investigation into how different environments impact the classification of human motion using radar micro-Doppler (MD) signatures. The environments studied include free space, through-the-wall, leaf tree foliage, and needle tree foliage. Results on presented on classification of the following three motions: crawling, walking, and jogging. The classification task was designed how to best separate these movements. The human motion data were acquired using a monostatic coherent Doppler radar operating in the C-band at 6.5 GHz from a total of six human subjects. The received signals were analyzed in the time-frequency domain using the Short-time Fourier Transform (STFT) which was used for feature extraction. Classification was performed using a Support Vector Machine (SVM) using a Radial Basis Function (RBF). Classification accuracies in the range 80-90% were achieved to separate the three movements mentioned.