毫米波雷达在复杂环境下的生命体征检测新方法
Non-contact Vital Signs Detection in Dynamic Environments
- 通过邻近峰谷估计时变直流偏移，结合希尔伯特与差分交叉乘法算法
- 低信噪比下仍能实现精准信号恢复，噪声抑制效果优于现有技术
- 适合动态环境中非接触式生命体征监测，如医疗监护、安防监控
毫米波雷达进行生命体征检测的关键在于精确的相位解调。然而，在复杂环境中，时变直流偏移和相位不平衡会严重降低解调性能。为此，本文提出一种新型直流偏移校准方法，结合希尔伯特变换与差分交叉乘法（HADCM）解调算法。该方法从相邻信号峰谷中估计时变直流偏移，并利用I/Q通道信号的差分形式与希尔伯特变换提取生命体征信息。仿真与实验结果表明，所提方法在低信噪比条件下仍保持稳健性能，相比现有解调技术，在挑战性场景下具有更高的信号恢复精度，并有效抑制噪声干扰。
原文摘要 · Abstract (English)
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.
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