Heart Rate Estimation and Performance Analysis using MIMO Radar with Dispersed Antennas

Heart rate (HR) is one of the most important indicators to assess the health condition of a person, so obtaining an accurate HR estimate is crucial. In this paper, a multiple-input multiple-output (MIMO) radar with dispersed antennas is employed to monitor the physiological signals caused by respiration and heartbeat for non-contact HR estimation. Fourier sine series is used to model the respiration and heartbeat signals measured by the MIMO radar, which enters the return signal from their impact on the human chest movement and incorporates a delay which is time-varying. Bayesian analysis is used for the HR estimation, and the corresponding Cramer-Rao bound (CRB) is derived. Via numerical studies, we show that applying the maximum likelihood (ML) estimation to estimate HR can lead to improved estimation performance over the existing HR estimation methods. The advantage of using MIMO radar for the HR estimation is also demonstrated.