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计算机工程 ›› 2021, Vol. 47 ›› Issue (11): 175-184. doi: 10.19678/j.issn.1000-3428.0060078

• 移动互联与通信技术 • 上一篇    下一篇

基于IR-UWB雷达的非接触式呼吸检测方法

党小超1,2, 张金龙1, 郝占军1,2, 安莹1   

  1. 1. 西北师范大学 计算机科学与工程学院, 兰州 730070;
    2. 甘肃省物联网工程研究中心, 兰州 730070
  • 收稿日期:2020-11-23 修回日期:2020-12-26 发布日期:2020-12-30
  • 作者简介:党小超(1963-),男,教授,主研方向为物联网、无线感知技术、传感器网络;张金龙,硕士研究生;郝占军(通信作者),教授;安莹,硕士研究生。
  • 基金资助:
    国家自然科学基金(61662070,61762079)。

Non-Contact Respiration Detection Method Based on IR-UWB Radar

DANG Xiaochao1,2, ZHANG Jinlong1, HAO Zhanjun1,2, AN Ying1   

  1. 1. College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China;
    2. Gansu Province Internet of Things Engineering Research Center, Lanzhou 730070, China
  • Received:2020-11-23 Revised:2020-12-26 Published:2020-12-30

摘要: 为消除脉冲超宽带(IR-UWB)雷达系统采集的人体呼吸回波信息中的干扰信号,并准确估计出人体呼吸频率和到达时间(TOA)范围,提出一种基于IR-UWB雷达的非接触式呼吸检测方法。对IR-UWB雷达回波信号进行线性趋势消除与滤波得到平滑的回波信号,在每个慢时间域上对回波信号使用傅里叶变换估计出人体呼吸频率,并设计基于回波信号均方根和超值峰度的EK-RMS算法确定TOA范围,同时将人体呼吸频率与TOA范围进行信息比对,最终得到受试目标的呼吸频率。实验结果表明,与Phase-Based、FFT和WT-Window算法相比,EK-RMS算法在低信噪比条件下具有更高的呼吸频率检测准确率和更强的鲁棒性,且对干扰信号有明显的抑制或消除作用。

关键词: 脉冲超宽带, 非接触式检测, 呼吸频率, 傅里叶变换, 均方根, 超值峰度

Abstract: The respiratory echo information collected by Impulse Radio Ultra Wide Band(IR-UWB) radar systems is often interfered by false signals.To eliminate interference,and estimate the range of the respiration frequency and Time of Arrival(TOA),a non-contact respiration detection method is proposed based on IR-UWB radar.By performing Linear Trend Subtraction(LTS) and filtering on IR-UWB radar echo signals,smooth echo signals are obtained.Then the respiration frequency is estimated by using Fourier Transformation(FT) for each slow time domain of the echo signal.Additionally,the range of TOA is determined by using the EK-RMS algorithm based on Excess Kurtosis(EK) and Root Mean Square(RMS) of the echo signal.On this basis,the range of TOA is compared with human respiration frequency,and finally the respiration frequency is obtained.Experimental results show that in the case of a low Signal-to-Noise Ratio(SNR),the EK-RMS algorithm exhibits a higher accuracy and robustness for respiration frequency detection than Phase-Based,FFT,and WT-Window algorithms.It can also significantly reduce or contain interference signals.

Key words: Impulse Radio Ultra Wide Band(IR-UWB), non-contact detection, respiration frequency, Fourier Transformation(FT), Root Mean Square(RMS), Excess Kurtosis(EK)

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