基于VMD的调频连续波雷达生命信号提取

针对生命探测雷达心跳信号能量微弱难于准确提取的问题，提出了一种基于变分模态分解(Variational Mode Decomposition, VMD)的调频连续波雷达生命信号提取算法。该算法首先利用距离维快速傅里叶变换(Fast Fourier Transform, FFT)获得距离剖面图，然后通过最大方差法得到目标所在距离门，接着对低通滤波后的相位信号使用VMD进行分离，并采用模态判别准则对生命信号进行重构，最后对重构信号进行FFT得到呼吸和心跳频率。雷达实测结果表明，相比于应用聚类经验模态分解(Ensemble Empirical Mode Decomposition, EEMD),所提生命信号提取算法能够有效抑制雷达回波中的呼吸谐波和噪声，更加准确有效地提取生命体征信号。

Life signal extraction for FMCW radar based on VMD

In order to solve the problem that the heartbeat signal has low energy and is difficult to extract accurately in the application of life detection radar,this paper proposes a life signal extraction method for frequency modulated continuous wave(FMCW) radar based on variational mode decomposition(VMD) algorithm.Firstly,the range profile is obtained by using the range fast Fourier transform(FFT).Secondly,the range bin of the target is determined by using the maximum variance method and the low-pass filtered phase signal is decomposed by the VMD algorithm.And then the life signal is reconstructed by using the mode judgement criterion.Finally,the respiratory and heart rate are obtained by performing FFT to the reconstructed signal.The experimental results show that the proposed algorithm can effectively suppress the respiratory harmonics and noise in radar echo and extract vital signs more accurately and effectively compared with the Ensemble Empirical Mode Decomposition(EEMD) algorithm.