基于IR-UWB雷达的非接触式呼吸检测方法

doi:10.19678/j.issn.1000-3428.0060078

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

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. 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 Xiaochao^1,2, ZHANG Jinlong¹, HAO Zhanjun^1,2, AN Ying¹

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/Abstract

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)

中图分类号:

TN958

党小超, 张金龙, 郝占军, 安莹. 基于IR-UWB雷达的非接触式呼吸检测方法[J]. 计算机工程, 2021, 47(11): 175-184.

DANG Xiaochao, ZHANG Jinlong, HAO Zhanjun, AN Ying. Non-Contact Respiration Detection Method Based on IR-UWB Radar[J]. Computer Engineering, 2021, 47(11): 175-184.

https://www.ecice06.com/CN/Y2021/V47/I11/175

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参考文献

[1] MOREY R M.Response to FCC 98-208 notice of inquiry in the matter of revision of part 15 of the commission's rules regarding ultra-wideband transmission systems:UCRL-ID-132691[R].[S.l.]:Office of Scientific and Technical Information,1998.
[2] HAO Z J,LI B B,DANG X C.A method for improving UWB indoor positioning[EB/OL].[2020-10-04].https://doi.org/10.1155/2018/8740872.
[3] 杨刚,朱士玲,李强,等.融合UWB与INS的消防员室内定位与NLOS检测算法[J].计算机工程,2021,47(9):153-161. YANG G,ZHU S L,LI Q,et al.Indoor firefighter positioning and NLOS detection algorithm based on UWB and INS[J].Computer Engineering,2021,47(9):153-161.(in Chinese)
[4] LIANG S D.Sense-through-wall human detection based on UWB radar sensors[J].Signal Processing,2016,126:117-124.
[5] LIANG X L,ZHANG H,FANG G Y,et al.An improved algorithm for through-wall target detection using ultra-wideband impulse radar[J].IEEE Access,2017,5:22101-22118.
[6] STADERINI E M.UWB radars in medicine[J].IEEE Aerospace and Electronic Systems Magazine,2002,17(1):13-18.
[7] 马琳.基于IR-UWB信号的穿墙目标定位方法研究[D].哈尔滨:哈尔滨工业大学,2009. MA L.Study of through-wall target localization method based on IR-UWB[D].Harbin:Harbin Institute of Technology,2009.(in Chinese)
[8] YAN J M,ZHAO H,LI Y S,et al.Through-the-wall human respiration detection using impulse ultra-wide-band radar[C]//Proceedings of 2016 IEEE Topical Conference on Biomedical Wireless Technologies,Networks,and Sensing Systems.Washington D.C.,USA:IEEE Press,2016:94-96.
[9] DROITCOUR A D,BORIC-LUBECKE O,LUBECKE V M,et al.0.25/spl mu/m CMOS and BiCMOS single-chip direct-conversion Doppler radars for remote sensing of vital signs[C]//Proceedings of 2002 IEEE International Solid-State Circuits Conference.Washington D.C.,USA:IEEE Press,2002:348-349.
[10] LUBECKE O B,ONG P W,LUBECKE V M.10 GHz Doppler radar sensing of respiration and heart movement[C]//Proceedings of the 28th Annual Northeast Bioengineering Conference.Washington D.C.,USA:IEEE Press,2002:55-56.
[11] REN L Y,KOO Y S,WANG H F,et al.Noncontact multiple heartbeats detection and subject localization using UWB impulse Doppler radar[J].IEEE Microwave and Wireless Components Letters,2015,25(10):690-692.
[12] 徐向阳.基于UWB生物雷达的心跳呼吸提取技术实现[D].西安:西安电子科技大学,2018. XU X Y.Realization on extracting technology of heartbeat and respiration based on UWB BioRadar[D].Xi'an:Xidian University,2018.(in Chinese)
[13] LI Z,LI W Z,LÜ H,et al.A novel method for respiration-like clutter cancellation in life detection by dual-frequency IR-UWB radar[J].IEEE Transactions on Microwave Theory and Techniques,2013,61(5):2086-2092.
[14] EL-BARDAN R,MALAVIYA D,DI RIENZO A.On the estimation of respiration and heart rates via an IR-UWB radar:an algorithmic perspective[C]//Proceedings of 2017 IEEE International Conference on Microwaves,Antennas,Communications and Electronic Systems.Washington D.C.,USA:IEEE Press,2017:1-5.
[15] LIU L B,LIU Z J,XIE H,et al.Numerical simulation of UWB impulse radar vital sign detection at an earthquake disaster site[J].Ad Hoc Networks,2014,13:34-41.
[16] CONTE E,FILIPPI A,TOMASIN S.ML period estimation with application to vital sign monitoring[J].IEEE Signal Processing Letters,2010,17(11):905-908.
[17] NEZIROVIC A,YAROVOY A G,LIGTHART L P.Signal processing for improved detection of trapped victims using UWB radar[J].IEEE Transactions on Geoscience and Remote Sensing,2010,48(4):2005-2014.
[18] 任晶晶.超宽带信号穿墙传播特性建模与检测技术研究[D].合肥:中国科学技术大学,2012. REN J J.Research on IR-UWB signal through-the-wall propagation characteristics modeling and detection techniques[D].Hefei:University of Science and Technology of China,2012.(in Chinese)
[19] LI C Z,LIN J.Random body movement cancellation in Doppler radar vital sign detection[J].IEEE Transactions on Microwave Theory and Techniques,2008,56(12):3143-3152.
[20] 陈德肯.基于雷达信号的非接触体征检测技术研究[D].北京:北京邮电大学,2019. CHEN D K.Research on non-contact vital signs detection technology using radar signals[D].Beijing:Beijing University of Posts and Telecommunications,2019.(in Chinese)
[21] XU Y Y,DAI S,WU S Y,et al.Vital sign detection method based on multiple higher order cumulant for ultrawideband radar[J].IEEE Transactions on Geoscience and Remote Sensing,2012,50(4):1254-1265.
[22] REN L Y,WANG H F,NAISHADHAM K,et al.Phase-based methods for heart rate detection using UWB impulse Doppler radar[J].IEEE Transactions on Microwave Theory and Techniques,2016,64(10):3319-3331.
[23] SHIKHSARMAST F,LÜ T T,LIANG X L,et al.Random-noise denoising and clutter elimination of human respiration movements based on an improved time window selection algorithm using wavelet transform[J].Sensors,2018,19(1):95.

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