Modeled gait variations in human micro-doppler

Measurement of human motion is important for security applications. One would like to observe humans unobtrusively and without privacy issues, and using radar provides one method to detect abnormal activity without using images. In this paper we focus on modeling the characteristics of human walking parameters in order to determine signature differences that are distinguishable and to determine the variability of normal walking to be compared to armed or loaded walking. We extract micro-Doppler from motion-captured human gait models and verify the models with radar measurements. We then vary the model to determine extent of normal micro-Doppler variation in multiple dimensions of human gait. We also characterize the ability of radar to determine gender and suggest that alternative views to the frontal view may be more discriminative.