A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar

We propose a robust super-resolution algorithm for vital sign radar in a low signal to noise ratio (SNR) environment. Conventional approaches, such as fast Fourier transform and super-resolution based algorithms, suffered to provide reliable results due to the limited data length and high noise leve...

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Main Authors: S. Yoon, B. Kim, S. Kim
Format: Article
Language:English
Published: Spolecnost pro radioelektronicke inzenyrstvi 2024-04-01
Series:Radioengineering
Subjects:
Online Access:https://www.radioeng.cz/fulltexts/2024/24_01_0155_0162.pdf
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author S. Yoon
B. Kim
S. Kim
author_facet S. Yoon
B. Kim
S. Kim
author_sort S. Yoon
collection DOAJ
description We propose a robust super-resolution algorithm for vital sign radar in a low signal to noise ratio (SNR) environment. Conventional approaches, such as fast Fourier transform and super-resolution based algorithms, suffered to provide reliable results due to the limited data length and high noise level. To overcome these limitations, our proposed algorithm utilizes a low-complexity least mean square (LMS) filter and relaxation (RELAX) techniques to achieve robust performance in low SNR environments. To evaluate the effectiveness of our algorithm, we conducted both simulation and experimental studies. Our results show that the proposed method significantly outperforms conventional methods, with Monte-Carlo simulations of respiration and heartbeat achieving an RMSE approximately 7 and 120 times lower than that of the conventional method, respectively. Overall, our algorithm provides a promising solution for robust vital sign detection in challenging low SNR environments.
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spelling doaj.art-4c0d6b2440b648e3ace979c30b63b1742024-04-22T22:12:15ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25122024-04-01331155162A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign RadarS. YoonB. KimS. KimWe propose a robust super-resolution algorithm for vital sign radar in a low signal to noise ratio (SNR) environment. Conventional approaches, such as fast Fourier transform and super-resolution based algorithms, suffered to provide reliable results due to the limited data length and high noise level. To overcome these limitations, our proposed algorithm utilizes a low-complexity least mean square (LMS) filter and relaxation (RELAX) techniques to achieve robust performance in low SNR environments. To evaluate the effectiveness of our algorithm, we conducted both simulation and experimental studies. Our results show that the proposed method significantly outperforms conventional methods, with Monte-Carlo simulations of respiration and heartbeat achieving an RMSE approximately 7 and 120 times lower than that of the conventional method, respectively. Overall, our algorithm provides a promising solution for robust vital sign detection in challenging low SNR environments.https://www.radioeng.cz/fulltexts/2024/24_01_0155_0162.pdfvital sign radarlms filterrelaxlow snrlow complexity
spellingShingle S. Yoon
B. Kim
S. Kim
A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar
Radioengineering
vital sign radar
lms filter
relax
low snr
low complexity
title A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar
title_full A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar
title_fullStr A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar
title_full_unstemmed A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar
title_short A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar
title_sort robust super resolution algorithm in a low snr environment for vital sign radar
topic vital sign radar
lms filter
relax
low snr
low complexity
url https://www.radioeng.cz/fulltexts/2024/24_01_0155_0162.pdf
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