摘要
针对调频连续波(FMCW)雷达工作带宽有限,难于对多目标生命信号准确检测的问题,提出了一种基于前后向空间平滑多重信号分类(FBSS-MUSIC)算法的FMCW雷达多目标生命信号检测方法。首先对中频信号进行距离维快速傅里叶变换(FFT)得到距离剖面矩阵,然后通过FBSS-MUSIC算法进行高分辨率距离估计从而确定每个目标所在的距离单元,接着根据每个目标所在的距离单元进行距离积分后提取每个目标对应的相位信号,使用变分模态分解(VMD)算法分解相位信号,通过模态判别准确重构呼吸和心跳信号,最后对生命信号进行短时傅里叶变换得到呼吸和心跳信号频率。实测数据结果表明,相比于距离维FFT,本文提出的算法能够显著提高FMCW雷达的距离分辨率,能够实现多个目标的准确定位并提取其生命体征信息。
In order to solve the problem of difficulty in extracting multi-target vital signs caused by the limited working bandwidth,a multi-target vital signs extraction method for frequency modulated continuous wave(FMCW)radar based on forward-backward spatial smoothing multiple signal classification(FBSS-MUSIC)is proposed.Firstly,the range dimension fast Fourier transform(FFT)is performed on the intermediate frequency signal to obtain the range profile.Then,the FBSS-MUSIC algorithm performs high-resolution range estimation to determine the range bin of each target and the phase signal corresponding to each target is obtained by integrating along the range dimension.The phase signal is decomposed by using the variational modal decomposition(VMD)algorithm and the life signal is reconstructed according to the mode judgement criterion.Finally,the short-time Fourier transform(STFT)is applied to estimate the frequency of the vital signal.The experimental results show that the proposed method can significantly improve the range resolution compared with the range-FFT and achieve the accurate range localization and vital signs extraction of multiple targets.
作者
屈乐乐
郭温文
QU Lele;GUO Wenwen(College of Electronic Information Engineering,Shenyang Aerospace University,Shenyang Liaoning 110136,China)
出处
《电子器件》
CAS
2024年第4期910-916,共7页
Chinese Journal of Electron Devices
基金
国家自然科学基金项目(61671310)
航空科学基金项目(2019ZC054004)
辽宁省兴辽英才计划项目基金项目(XLYC1907134)
辽宁省百千万人才工程项目基金项目(2018B21)。
关键词
调频连续波雷达
多重信号分类
前后向空间平滑
生命信号
变分模态分解
frequency modulated continuous wave radar
multiple signal classification
forward-backward spatial smoothing
life signal
variational modal decomposition
