Cyclostationary Approach for Heart and Respiration Rates Monitoring with Body Movement Cancellation Using Radar Doppler System

Heart and respiration rate measurement using Doppler radar is a non-contact and non-obstructive way for remote thorough-clothing monitoring of vital signs. The modulated back-scattered radar signal in the presence of high noise and interference is non-stationary with hidden periodicities, which cannot be detected by ordinary Fourier analysis. In this paper we propose a cyclostationary approach for such signals and show that by using non-linear transformation and then Fourier analysis of the radar signal, the hidden periodicities can be accurately obtained. Numerical results show that the vital signs can be extracted as cyclic frequencies, independent of SNR and without any filtering or phase unwrapping.

💡 Research Summary

The paper addresses a fundamental challenge in non‑contact vital‑sign monitoring using continuous‑wave (CW) Doppler radar: the received baseband I‑Q signal becomes highly non‑stationary when the subject is clothed, when environmental noise is strong, and when the subject makes small random body movements. Under these conditions the heart‑beat and respiration components are hidden; conventional Fourier analysis fails to reveal distinct spectral lines, and standard processing pipelines (filtering, phase unwrapping, demodulation) become unreliable, especially at low signal‑to‑noise ratios (SNR).

To overcome this, the authors propose a cyclostationary signal‑processing framework. They model the chest displacement due to heartbeat and breathing as two cosine terms, (h(t)=a_h\cos(2\pi f_h t)) and (r(t)=a_r\cos(2\pi f_r t)). The radar return phase is proportional to the sum of these displacements, plus a random motion term (x(t)) (modeled as a uniform 1‑D process that approximates 2‑D motion) and phase noise (\phi_n(t)). The complex baseband signal is written as

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