模态联合空域估计的毫米波雷达呼吸心率检测  

Modal joint airspace estimation for respiration andheart rate detection by millimeter wave radar

作　　者：廖涛 万相奎[1] 贡文新 武明虎[1] 王滨辉 LIAO Tao;WAN Xiang-kui;GONG Wen-xin;WU Ming-hu;WANG Bin-hui(Hubei Power Grid Intelligent Control and Equipment Engineering Technology Research Center,Hubei University of Technology,Wuhan 430068,China)

机构地区：[1]湖北工业大学湖北省电网智能控制与装备工程技术研究中心,湖北武汉430068

出　　处：《陕西科技大学学报》2024年第3期188-196,共9页Journal of Shaanxi University of Science & Technology

基　　金：湖北省自然科学基金项目(2022CFA007);湖北省武汉市知识创新专项项目(2022020801010258)。

摘　　要：在毫米波雷达检测人体呼吸率和心率过程中,周围环境存在的静态杂波使得雷达极难分辨人体胸腔运动信息,从而影响了呼吸信号和心跳信号的分离.同时,由于呼吸信号在高频带的谐波分量与心跳信号所处低频带部分的频率相近,很难分离.为解决上述问题,提出了一种模态联合空域估计的检测方法,主要采用单轮集成经验模态分解(SEEMD)算法将胸腔相位信号分解为各模态分量,以消除静态杂波对呼吸心跳信号的影响,再采用多重信号分类(MUSIC)算法将心跳模态分量信号由时域转换到空域中估计其频率,以消除呼吸谐波的影响.实验结果表明,本方法检测下的呼吸率准确率为95.76%,心率准确率为98.76%.与传统算法相比,本文所提方法下的呼吸率和心率估计更为准确.In the process of detecting human respiration and heart rate using millimeter wave radar,the static clutter in the environment makes it extremely difficult for the radar to discriminate the information about the movement of the human chest cavity,which affects the separation of respiration and heart rate signals.At the same time,it is difficult to separate the harmonic components of the respiration signal in the high-frequency band and the heartbeat signal in the low-frequency band because the frequencies of the harmonic components in the high-frequency band are similar.To solve the above problems,this paper proposes a joint modal spatial domain estimation detection method,which mainly adopts an single ensemble empirical modal decomposition(SEEMD)algorithm to decompose the thoracic phase signal into each modal component to eliminate the influence of static noise on the respiratory heartbeat signal,and then uses a multiple signal classification(MUSIC)algorithm to convert the heartbeat modal component signals from the time domain to the spatial domain to estimate their frequencies to eliminate the influence of respiratory harmonics.The experimental results show that the accuracy of respiratory rate under the detection of this paper's method is 95.76%,and the accuracy of heart rate is 98.76%.Compared with the traditional algorithms,the proposed method is more accurate in estimating respiratory rate and heart rate.

关 键 词：毫米波雷达 单轮集成经验模态分解 多重信号分类 

分 类 号：TN953.2[电子电信—信号与信息处理]