基于FMCW雷达的自适应生命信号提取方法  

Adaptive Vital Signal Extraction Method Based on FMCW Radar

作　　者：杨俊 黄俊[1,2] 陶威 YANG Jun;HUANG Jun;TAO Wei(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Chongqing Key Laboratory of Signal and Information Processing,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065 [2]重庆邮电大学信号与信息处理重庆市重点实验室,重庆400065

出　　处：《雷达科学与技术》2022年第2期187-194,201,共9页Radar Science and Technology

基　　金：国家自然科学基金(No.61771085)。

摘　　要：为了进一步提高调频连续波(FMCW)雷达自适应提取生命信号能力,通过提高距离分辨率提取被测目标位置距离维处的人体生命信号,利用改进的快速互补集合经验模态分解(IFCEEMD)对生命信号分解,从分解得到的若干个固有模态函数(IMFs)中利用筛选准则分离出呼吸、心跳信号。实验结果表明,所提出的方法能够快速、准确地提取出不同呼吸状态下的呼吸频率和心跳频率,并且有效地消除人体身体随机抖动带来的干扰。To improve the adaptive extraction ability of vital signal of frequency modulated continuous wave(FMCW)radar,the vital signal of human body at the distance dimension of the measured target position is extracted by improving the range resolution of the radar.The vital signal is decomposed by improved fast complementary ensemble empirical mode decomposition(IFCEEMD).Respiratory and heartbeat signals are separated by the screening criteria from several intrinsic mode functions(IMFs).Experimental results show that the proposed method can quickly and accurately extract respiration frequency and heartbeat frequency under different breathing states,and effectively eliminate the interference caused by random body shaking.

关 键 词：调频连续波雷达 生命信号 人体随机抖动 改进的快速互补集合经验模态分解 

分 类 号：TN959.6[电子电信—信号与信息处理]