Non-contact Vital Signs Detection in Dynamic Environments
This work addresses the challenge of non-contact vital signs monitoring in dynamic settings, which is important for healthcare and surveillance applications, but it appears incremental as it builds on existing demodulation methods.
The paper tackled the problem of accurate phase demodulation for vital sign detection using millimeter-wave radar in complex environments, where time-varying DC offsets and phase imbalances degrade performance, and demonstrated that the proposed method maintains robust performance under low signal-to-noise ratios with more accurate signal recovery compared to existing techniques.
Accurate phase demodulation is critical for vital sign detection using millimeter-wave radar. However, in complex environments, time-varying DC offsets and phase imbalances can severely degrade demodulation performance. To address this, we propose a novel DC offset calibration method alongside a Hilbert and Differential Cross-Multiply (HADCM) demodulation algorithm. The approach estimates time-varying DC offsets from neighboring signal peaks and valleys, then employs both differential forms and Hilbert transforms of the I/Q channel signals to extract vital sign information. Simulation and experimental results demonstrate that the proposed method maintains robust performance under low signal-to-noise ratios. Compared to existing demodulation techniques, it offers more accurate signal recovery in challenging scenarios and effectively suppresses noise interference.