Concurrent Respiration Monitoring of Multiple Subjects by Phase-Comparison Monopulse Radar Using Independent Component Analysis (ICA) With JADE Algorithm and Direction of Arrival (DOA)

While non-contact monitoring of human respiration has been demonstrated using Doppler radar, the concurrent monitoring of multiple equidistant subjects remains a significant technological challenge. Reported research has so far been limited to maintaining 1-m subject separation, based on the radar a...

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Bibliographic Details
Published inIEEE access Vol. 8; pp. 73558 - 73569
Main Authors Islam, Shekh M. M., Boric-Lubecke, Olga, Lubekce, Victor M.
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Antenna arrays
Beam switching
Direction of arrival
direction of arrival (DOA)
Direction-of-arrival estimation
Doppler radar
Independent component analysis
joint approximate diagonalization of eigenmatrices (JADE)
Meters
Monitoring
Monopulse radar
non-contact measurement
Radar antennas
Radar beams
Radar signatures
Receivers
Respiration
respiration monitoring
Separation
subject separation
vital signs
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Summary:While non-contact monitoring of human respiration has been demonstrated using Doppler radar, the concurrent monitoring of multiple equidistant subjects remains a significant technological challenge. Reported research has so far been limited to maintaining 1-m subject separation, based on the radar antenna beam-width. Proposed here is a hybrid method consisting of an SNR-based intelligent decision algorithm which integrates two different approaches to isolate respiratory signatures of two subjects within the radar beam-width separated by less than 1 meter. Using Independent Component Analysis with the JADE algorithm (ICA-JADE) and Direction of Arrival (DOA), this SNR-based decision algorithm works with an accuracy above 93%. In addition, angular location of each subject is estimated by phase-comparison monopulse and an integrated beam switching capability is demonstrated to optimally extract respiratory information. The proposed method coherently combines two separation methods to overcome multiple-subject monitoring limits which can lead to practical adoption for many respiration monitoring applications.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2988038