基于盲源分离的多人呼吸信号检测方法

杨轩 王子颖 张力 赵恒 洪弘

杨轩, 王子颖, 张力, 等. 基于盲源分离的多人呼吸信号检测方法[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR24115
引用本文: 杨轩, 王子颖, 张力, 等. 基于盲源分离的多人呼吸信号检测方法[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR24115
YANG Xuan, WANG Ziying, ZHANG Li, et al. Noncontact multiperson respiratory detection method based on blind source separation[J]. Journal of Radars, in press. doi: 10.12000/JR24115
Citation: YANG Xuan, WANG Ziying, ZHANG Li, et al. Noncontact multiperson respiratory detection method based on blind source separation[J]. Journal of Radars, in press. doi: 10.12000/JR24115

基于盲源分离的多人呼吸信号检测方法

DOI: 10.12000/JR24115
基金项目: 国家自然科学基金(62431013, 62301255, 62201259),江苏省自然科学基金(BK20220942, BK20220940),中央高校基本科研业务费专项资金(30923011026, 30923011006)
详细信息
    作者简介:

    杨 轩,博士生,主要研究方向为非接触式生命体征探测、雷达信号处理等

    王子颖,硕士生,主要研究方向为生物医学传感和雷达信号处理等

    张 力,博士,工程师,主要研究方向为基于雷达信号处理的杂波抑制、非接触式生命体征探测以及人体动作识别和目标识别

    赵 恒,博士,讲师,主要研究方向为生物医学传感、非接触式生命体征探测以及雷达信号处理等

    洪 弘,博士,教授,主要研究方向为生物医学传感、语音信号处理以及雷达信号处理等

    通讯作者:

    赵恒 soniczhao@live.com

    洪弘 hongnju@njust.edu.cn

  • 责任主编:方震 Corresponding Editor: FANG Zhen
  • 中图分类号: TN957.52

Noncontact Multiperson Respiratory Detection Method Based on Blind Source Separation

Funds: The National Natural Science Foundation of China (62431013, 62301255, 62201259), Natural Science Foundation of Jiangsu Province (BK20220942, BK20220940), Fundamental Research Funds for the Central Universities (30923011026, 30923011006)
More Information
  • 摘要: 近年来,人们越来越关注多人环境下的呼吸监测,以及如何同时监测多人的健康状态。在多人呼吸检测的算法中,盲源分离算法因其无需先验信息并且对硬件性能依赖性较小而备受研究者关注。然而,在多人呼吸监测场景中,目前的盲源分离算法通常将相位信号作为源信号进行分离,该文引入FMCW雷达下距离维信号和相位信号的对比,推导出相位信号作为源信号存在近似误差,并通过仿真验证距离维信号作为源信号时分离效果更好。另外,该文提出了基于非圆复数独立成分分析的多人呼吸信号分离算法,分析了不同呼吸信号参数对分离效果的影响,仿真和实测实验表明,所提出的方法适用于天线个数不小于目标个数时多人呼吸信号的检测,并且在目标角度差为9.46°时,也能够准确分离呼吸信号。

     

  • 图  1  均匀线阵示意图

    Figure  1.  Schematic diagram of uniform linear array

    图  2  多人呼吸分离的总体原理图

    Figure  2.  Overall schematic diagram for multiperson respiration detection

    图  3  两天线两目标复数盲源分离效果图

    Figure  3.  Effect diagram of complex blind source separation with two antennas

    图  4  呼吸信号及呼吸参考信号对比

    Figure  4.  Comparison of the respiratory signals and respiratory reference signals

    图  5  基于相位信号恢复的呼吸信号及呼吸参考信号对比

    Figure  5.  Comparison of respiratory signal and respiratory reference signal based on phase signal recovery

    图  6  3天线3目标恢复的呼吸信号及呼吸参考信号对比

    Figure  6.  Comparison of the respiratory signals and respiratory reference signals recovered from three antennas and three subjects

    图  7  不同信噪比下信号重构的误差

    Figure  7.  Error of signal reconstruction under different signal-to-noise ratios

    图  8  不同呼吸参数下的波形重构误差

    Figure  8.  Error of signal reconstruction under different respiratory parameters

    图  9  矽典微24 G雷达实物图

    Figure  9.  Physical image of the 24 G radar from Iclegend Micro

    图  10  实际测试场景

    Figure  10.  Actual testing scene

    图  11  1 m处双人正对雷达时分离出的呼吸波形以及参考波形

    Figure  11.  Respiratory waveforms and reference waveforms separated at 1 m when two individuals face the radar directly

    图  12  1 m处双人正对雷达时分离前后的星座图

    Figure  12.  Constellation diagrams before and after separation when two individuals face the radar directly at 1 m

    图  13  1 m处双人侧对雷达时分离出的呼吸波形以及参考波形

    Figure  13.  Respiratory waveforms and reference waveforms separated at 1 m when two individuals face the radar sideways

    图  14  1 m处双人背对雷达时分离出的呼吸波形以及参考波形

    Figure  14.  Respiratory waveforms and reference waveforms separated at 1 m when two individuals face away from the radar

    图  15  呼吸异常时雷达分离出的呼吸波形以及参考波形

    Figure  15.  Respiratory waveforms and reference waveforms separated by radar during abnormal respiration

    图  16  10 min内雷达得到的两个测试者的呼吸率以及参考呼吸率

    Figure  16.  The respiratory rates of two testers obtained by radar within 10 minutes, along with the reference respiratory rate

    图  17  两人距离雷达1.8 m场景示意图

    Figure  17.  Illustration of two people at a distance of 1.8 m from the radar

    图  18  两人距离雷达1.8 m时分离出两人的雷达呼吸信号以及呼吸参考信号

    Figure  18.  Radar respiratory signals of two persons separated when the distance to the radar is 1.8 m, and the reference respiratory signal

    图  19  两人呼吸频率一致时分离出两人的雷达呼吸信号以及呼吸参考信号

    Figure  19.  Radar respiratory signals of two persons separated when their respiratory frequencies are consistent, and the reference respiratory signal

    图  20  两人距离雷达1.8 m和2 m场景示意图

    Figure  20.  Illustration of two people at a distance of 1.8 m and 2.0 m from the radar

    图  21  1.8 m处两个目标的呼吸波形及角度

    Figure  21.  Respiratory waveforms and angles of two subjects at 1.8 m

    图  22  2 m处两个目标的呼吸波形及角度

    Figure  22.  Respiratory waveforms and angles of two subjects at 2 m

    1  多人呼吸分离算法流程

    1.   Steps of complex multiperson blind source separation algorithm

     输入:N个天线的距离维信号X
     输出:分离后的N个目标的距离维信号
     初始化:初始化解混矩阵${{\boldsymbol{W}}^{\text{H}}} = \left[ {{{\boldsymbol{w}}_1} \;{{\boldsymbol{w}}_2}\; \cdots\; {{\boldsymbol{w}}_N}} \right] = {\boldsymbol{I}}$
     1 通过式(18)对观测数据X进行白化,得到Z
     2 令$k = 1$
     3 使用式(25)对$ {{\boldsymbol{w}}_i} $进行更新,直到满足收敛条件
     4 $k = k + 1$,使用步骤3完成下一个列向量的估计
     5 完成所有分量分离,并使用式(26)进行正交变换
     6 得到混合矩阵的估计$ \tilde {\boldsymbol{A}} = {{\boldsymbol{V}}^{ - 1}}{\boldsymbol{W}} $,以及源信号的估计
     $ {\boldsymbol{Y}} = {{\boldsymbol{W}}^{\text{H}}}{\boldsymbol{Z}} $
     7 按照式(28)和式(29)去除相位模糊
    下载: 导出CSV

    表  1  仿真实验参数

    Table  1.   Simulation experiment parameters for two antennas and two targets

    参数 数值
    载频 24 GHz
    天线阵元个数 2
    天线间距 $\lambda /2$
    下载: 导出CSV

    表  2  不同目标个数、不同天线数量时峭度和

    Table  2.   Sum of kurtosis for different number of targets, different number of antennas

    天线个数1个目标2个目标3个目标
    11.001.501.75
    21.002.352.77
    31.002.353.48
    下载: 导出CSV

    表  3  FMCW雷达硬件参数设置

    Table  3.   Hardware parameters setting for FMCW radar

    参数 数值
    起始频率 24 GHz
    带宽 1 GHz
    Chirp采样点个数 1024
    ADC采样速率 2.5 MHz
    Chirp重复周期 10 ms
    下载: 导出CSV
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出版历程
  • 收稿日期:  2024-06-05
  • 修回日期:  2024-08-21
  • 网络出版日期:  2024-09-24

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