ECG Signal Detection Method Based on Millimeter Wave Radar

Abstract

In the medical field, the detection of breathing and heartbeat signals is very important. This paper analyzes and verifies a method for detecting and estimating characteristic parameters of heartbeat signals based on millimeter wave radar, and analyzes the effect of decomposing respiratory and heartbeat signals based on wavelet changes and empirical mode decomposition. Perform range FFT on the radar echo signal to obtain the range-time image of the target, and then estimate the center of the constellation based on the method.The least squares approximation algorithm based on iterative weighting is used to eliminate the static clutter of the actual FMCW radar signal. Then the target is detected in the azimuth by the capon algorithm, and the CFAR detection is performed to extract the echo signal on the unit of distance where the target is located. The target signal is phase demodulated to obtain the phase information of micro-motions such as breathing and heartbeat. The wavelet transform is used to decompose the breathing and heartbeat signals from the phase information, and the short-term average amplitude difference function frequency estimation method is used to estimate the frequency of breathing and heartbeat.