High-Precision Vital Signs Detection Method Based on Spectrum Refinement and Extended DCMA

In this paper, the spectral estimation algorithm is extended to the detection of human vital signs by mm-wave frequency modulated continuous wave (FMCW) radar, and a comprehensive algorithm based on spectrum refinement and the extended differentiate and cross multiply algorithm (DCMA) has been proposed. Firstly, the improved DFT algorithm is used to accurately obtain the distance window of human body. Secondly, phase ambiguity in phase extraction is avoided based on extended DCMA algorithm. Then, the spectrum range of refinement is determined according to the peak position of the spectrum, and the respiratory and heartbeat frequency information is obtained by using chirp z-transform (CZT) algorithm to perform local spectrum refinement. For verification, this paper has simulated the radar echo signal modulated by the simulated cardiopulmonary signal according to the proposed algorithm. By recovering the simulated cardiopulmonary signal, the high-precision respiratory and heartbeat frequency have been obtained. The results show that the proposed algorithm can effectively restore human breathing and heartbeat signals, and the relative error of frequency estimation is basically kept below 1.5%.