华南理工大学学报(自然科学版) ›› 2010, Vol. 38 ›› Issue (10): 1-6.doi: 10.3969/j.issn.1000-565X.2010.10.001

• 电子、通信与自动控制 •    下一篇

基于经验模态分解的生命信号提取算法

冯久超 潘水洋   

  1. 华南理工大学 电子与信息学院, 广东 广州 510640
  • 收稿日期:2009-12-31 修回日期:2010-03-08 出版日期:2010-10-25 发布日期:2010-10-25
  • 通信作者: 冯久超(1964-),男,教授,博士生导师,主要从事数字信号处理研究. E-mail:fengjc@scut.edu.cn
  • 作者简介:冯久超(1964-),男,教授,博士生导师,主要从事数字信号处理研究.
  • 基金资助:

    国家自然科学基金资助项目(60872123); NSFC-广东省自然科学联合基金资助项目(U0835001)

Extraction Algorithm of Vital Signals Based on Empirical Mode Decomposition

Feng Jiu-chao  Pan Shui-yang   

  1. School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2009-12-31 Revised:2010-03-08 Online:2010-10-25 Published:2010-10-25
  • Contact: 冯久超(1964-),男,教授,博士生导师,主要从事数字信号处理研究. E-mail:fengjc@scut.edu.cn
  • About author:冯久超(1964-),男,教授,博士生导师,主要从事数字信号处理研究.
  • Supported by:

    国家自然科学基金资助项目(60872123); NSFC-广东省自然科学联合基金资助项目(U0835001)

摘要: 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.

关键词: 生命信号, 信号提取, 多普勒雷达, 经验模态分解

Abstract:

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.

Key words: vital signal, signal extraction, Doppler radar, empirical mode decomposition