Simulation and Signal Processing of Through Wall UWB radar for Human Being's Periodic Motions Detection

摘要

The human's Micro-Doppler signatures resulting from breathing, arm, foot and other periodic motion can provide valuable information about the structure of the moving parts and may be used for identification and classification purposes. In this paper, we carry out simulate with FDTD method and through wall experiment with UWB radar for human being's periodic motion detection. In addition, Advancements signal processing methods are presented to classify and to extract the human's periodic motion characteristic information, such as Micro-Doppler shift and motion frequency. Firstly, we apply the Principal Component Analysis (PCA) with singular value decomposition (SVD) to de-noise and extract the human motion signal. Then, we present the results base on the Hilbert-Huang transform (HHT) and the S transform to classify and to identify the human's micro-Doppler shift characteristics. The results demonstrate that the combination of UWB radar and various processing methods has potential to detect human's Doppler signatures effectively.