太赫兹频段下基于EMD的人体生命特征检测

非接触式的心跳呼吸信号检测对重症患者心跳呼吸的远程监控、自然灾害中受害者的搜寻等都有重要的应用。本文针对人体心跳呼吸信号相对于复杂环境属于微弱信号的情况，提出了一种太赫兹频段下基于经验模态分解(EMD)的人体生命特征检测方法。首先建立太赫兹雷达人体目标回波模型，对回波信号进行经验模态分解。然后进行时频分析，得到心跳呼吸微多普勒信息，提取其频谱质心曲线。再做第二次时频分析，实现心跳呼吸频率的提取与分离。在高斯杂波环境中进行了仿真实验，检测结果表明，基于EMD的检测方法与直接检测方法相比，取得了更好的检测效果，具有较强抗噪能力，适合于微弱信号处理。 

Human Life Feature Detection Based on EMD Method in THz Band

Non-contact respiration and heartbeat signal detection could be applied to search for victims in the disaster or the remote monitoring of the respiration and heartbeat of a patient. Considered the human respiration and heartbeat signal is weak signal compared to the complex environment, we proposed a human life feature detection method based on EMD in THz band. A human target echo model for THz radar was established firstly, and a time-frequency analysis of the echo after empirical mode decomposition will yield a signal. The centroid curve of this signal underwent a second time-frequency analysis to extract and separate the heart and breath rates of the individual. The simulation carried out in Gaussian clutter background show that the detection method based on EMD has a better performance than the direct detection method. It has the strong ability to resist noise and is suitable for weak signal processing.