Noncontact Heartbeat and Respiratory Signal Separation Using a Sub 6 GHz SDR Micro-Doppler Radar

Abstract

Software-defined radio (SDR) can be used to detect human respiratory and heartbeat signals with the merits of low costs, high flexibility, and fast implementation. This paper proposes a human respiratory heartbeat detection system based on SDR micro-Doppler radar. The system can adjust radar parameters in real-time according to the detection environment, breaking the hardware limitations of traditional radar. Data pre-processing is performed on the transmit and receive baseband signals to obtain a composite signal containing human respiratory and heartbeat signals. In addressing the difficulty of detecting heartbeat signals compared to respiratory signals, an adaptive heartbeat signal enhancement detection algorithm named the one-time differential weighted step-size normalized least mean square (ODWS-NLMS) is proposed. This algorithm enhances the step size through weighted improvements utilizing the first-order differential characteristics of composite signals. Experiments were conducted in three distinct real-world environments, and the results indicate that the proposed algorithm outperforms discrete wavelet transform (DWT) and ensemble empirical mode decomposition (EEMD) in terms of average accuracy, root mean square error (RMSE), and signal-to-noise ratio (SNR).