Abstract: To solve the problem that the interference between millimeter wave radars will cause the weak vital sign signal obtained by bioradar to be submerged, resulting in the inability to accurately measure respiration and heartbeat, a method is proposed based on improved singular spectrum analysis to suppress the interference between radars, and the target beat signal is reconstructed from the interfered signal through correlation calculation to suppress the interference and eliminate the background noise. Furthermore, an ensemble empirical mode decomposition method based on information entropy is proposed to eliminate the residual phase noise of the beat signals, and the respiration and heartbeat signals are selected from the intrinsic mode function components after ensemble empirical mode decomposition through information entropy calculation to suppress the residual noise. Experimental results show that the proposed method can effectively recover the respiration and heartbeat signals from the interfered signals, and improve the signal-to-noise ratios of respiration and heartbeat. Therefore, the methods proposed in this research improve the anti-interference ability of bioradar and enhance the practicability of bioradar.

Key words: millimeter wave bioradar, vital sign detection, interference suppression, singular spectrum analysis, ensemble empirical mode decomposition