Doppler radar-based fast heart rate (HR) extraction has great application potential in stress and emotion recognition, anxiety treatments, etc. However, fast extraction of HR is still a great challenge for the vital sign detection applying the traditional discrete Fourier transform (DFT) method based on a continuous-wave (CW) Doppler radar sensor. When applying traditional DFT to the baseband signal analysis, the spectrum resolution will become insufficient if the time window is less than 10 s. In this paper, an interpolated DFT algorithm based on a poly-item cosine window is introduced to achieve fast extraction of HR with only 3 s data length. In addition, the leakage and grid effect phenomenon is presented to show the defects caused by the traditional DFT method. To verify the effectiveness of the proposed method, simulations are performed and experiments are executed using a 10-GHz CW Doppler radar sensor platform. Compared with the traditional DFT method, the interpolated DFT method reduces the average HR error from 8.48% to 1.87% based on the Hanning window and from 8.48% to 1.45% based on the rectangular window.

中文翻译：

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连续多普勒雷达插值离散傅里叶变换算法快速提取心率

基于多普勒雷达的快速心率（HR）提取在压力和情绪识别，焦虑治疗等方面具有巨大的应用潜力。然而，对于采用传统离散傅里叶变换（DFT）的生命体征检测，快速提取HR仍然是一个巨大的挑战连续波（CW）多普勒雷达传感器）。将传统DFT应用于基带信号分析时，如果时间窗口小于10 s，频谱分辨率将变得不足。本文介绍了一种基于多项目余弦窗的插值DFT算法，以仅3 s的数据长度实现HR的快速提取。此外，提出了漏电和网格效应现象，以显示传统DFT方法引起的缺陷。为了验证所提出方法的有效性，使用10 GHz连续波多普勒雷达传感器平台进行仿真并执行实验。与传统的DFT方法相比，插值DFT方法将基于Hanning窗口的平均HR误差从8.48％降低到1.87％，基于矩形窗口的平均HR误差从8.48％降低到1.45％。