穿墙生命探测雷达系统中,传统的基于快速傅里叶变换（FFT）的生命信号提取算法不能有效处理非平稳信号,且易受呼吸谐波干扰.为此,文中提出了一种从时域上提取生命信号的新方法.首先应用经验模态分解（EMD）将雷达接收信号分解成有限个固有模态函数（IMF）,再用反映生命信号结构特征的IMF分量从时域上分别重构呼吸与心跳信号.仿真结果表明,所提出的新方法能避免呼吸信号谐波对心跳信号的干扰,因而能更加精确地提取心跳信号.

As the conventional FFT-based extraction algorithm of vital signals for the through-wall detection radar（TWDR） is insufficient in handling non-stationary signals and is sensitive to respiration harmonic interference,a novel method to extract vital signals is proposed based on the empirical mode decomposition（EMD）.In this method,the vital signal accepted by the radar is decomposed into several intrinsic mode functions（IMFs） via the EMD,and the IMF components describing the structural characteristics of the vital signal are used to reconstruct respiration and heartbeat signals in the time domain.Simulated results indicate that the proposed method helps to extract heartbeat signals with high accuracy because it effectively eliminates the interference of respiration harmonics.