Multitarget Respiration Monitoring Based on Cumulative Phase Gradient Approach

Abstract

Simultaneous measurements of multi-target vital signs have been quite challenging for radar-based non-contact vital signs monitoring. This paper presents a novel cumulative phase gradient approach for accurate estimates of multi-target respirations without either range or beam discrimination in a single-input single-output (SISO) radar sensor. The signal model of multi-target respiration is first provided, and then a cumulative phase gradient approach is developed to accurately estimate multi-target respirations from the observed mixtures by exploiting the underlying periodicity of the respiration waveforms. The proposed method provides average estimated error rates around 3% in the experiment with closely located three human targets within range resolution, and demonstrates its significant superiorities over other methods.