Noncontact Respiratory Measurement for Multiple People at Arbitrary Locations Using Array Radar and Respiratory-Space Clustering

In this study, we develop a noncontact measurement system for monitoring the respiration of multiple people using millimeter-wave ultrawideband array radar. To separate the radar echoes of multiple people, conventional techniques cluster the radar echoes in the time, frequency, or spatial domain. Focusing on the measurement of the respiratory signals of multiple people, we propose a method called respiratory-space clustering in which individual differences in the respiratory rate are effectively exploited to accurately resolve the echoes from human bodies. The proposed respiratory-space clustering can separate echoes, even when people are located close to each other. In addition, the proposed method can be applied when the number of targets is unknown and can accurately estimate the number of people and their positions. We perform measurements under two scenarios involving five and seven participants to verify the performance of the proposed method, and quantitatively evaluate the estimation accuracy of the number of people and the respiratory intervals. The experimental results show that the root-mean-square error in estimating the respiratory interval is 172 ms on an average. The proposed method improves the estimation accuracy of the number of people by 85.0% compared to the conventional method, demonstrating the high-precision measurement of the respiration of several people.