摘要详情

ID / 提交时间

18 / 2024-08-09 21:14:35

标题

A vital signs denoising algorithm for FMCW radar based on BKA-VMD combined wavelet threshold

关键字

BKA, FMCW radar, VMD, Vital signs signal, Wavelet threshold denoising

主题及专题

Special Sessions > SS08 Advanced Signal Processing Technologies Based on AI and Its Applications

状态

全文录用

作者

XieMin / Xidian University

DuXIaowen / Xidian University

陈怡铭 / 同济大学

李雪峰 / 同济大学

ZHAOMeng / Xidian University

JiJing / Xidian University

摘要

FMCW radar has excellent ranging and velocity measurement capabilities, combining the velocity resolution of CW radar with the range resolution of UWB radar, and possesses strong anti-interference ability. It does not require contact with any electrodes or sensors when working, offering strong penetration and good privacy. This enables the detection of human vital signs information from a long distance, making it highly valuable for non-contact vital signs detection. But during detection, the chest displacements caused by respiration and the heartbeat is relatively small, besides heartbeat signals can be easily interfered by respiratory harmonics and other noises. A denoising method combining Black-winged Kite Algorithm (BKA) optimized Variational Mode Decomposition (VMD) algorithm and wavelet threshold denoising is introduced for the first time on the issue. Experimental results indicate that when the SNR is 0, the algorithm is compared and analyzed with the EMD joint wavelet thresholding algorithm ，the correlation coefficient improves by 4.36%, the signal-to-noise ratio improves by 5.342dB, and the root-mean-square reduces by 0.7606, which retains more vital signs information while having higher signal-to-noise ratio, and it can be effectively used in the field of vital signs detection.