Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar
Radar-based non-contact vital signs monitoring has great value in through-wall detection applications. This paper presents the theoretical and experimental study of through-wall respiration and heartbeat pattern extraction from multiple subjects. To detect the vital signs of multiple subjects, we em...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/15/2905 |
| _version_ | 1797525170107187200 |
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| author | Zhi Li Tian Jin Yongpeng Dai Yongkun Song |
| author_facet | Zhi Li Tian Jin Yongpeng Dai Yongkun Song |
| author_sort | Zhi Li |
| collection | DOAJ |
| description | Radar-based non-contact vital signs monitoring has great value in through-wall detection applications. This paper presents the theoretical and experimental study of through-wall respiration and heartbeat pattern extraction from multiple subjects. To detect the vital signs of multiple subjects, we employ a low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) imaging radar and derive the relationship between radar images and vibrations caused by human cardiopulmonary movements. The derivation indicates that MIMO radar imaging with the stepped-frequency continuous-wave (SFCW) improves the signal-to-noise ratio (SNR) critically by the factor of radar channel number times frequency number compared with continuous-wave (CW) Doppler radars. We also apply the three-dimensional (3-D) higher-order cumulant (HOC) to locate multiple subjects and extract the phase sequence of the radar images as the vital signs signal. To monitor the cardiopulmonary activities, we further exploit the VMD algorithm with a proposed grouping criterion to adaptively separate the respiration and heartbeat patterns. A series of experiments have validated the localization and detection of multiple subjects behind a wall. The VMD algorithm is suitable for separating the weaker heartbeat pattern from the stronger respiration pattern by the grouping criterion. Moreover, the continuous monitoring of heart rate (HR) by the MIMO radar in real scenarios shows a strong consistency with the reference electrocardiogram (ECG). |
| first_indexed | 2024-03-10T09:09:58Z |
| format | Article |
| id | doaj.art-3d349dae7dd849ebb11fcde86423766e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T09:09:58Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-3d349dae7dd849ebb11fcde86423766e2023-11-22T06:05:55ZengMDPI AGRemote Sensing2072-42922021-07-011315290510.3390/rs13152905Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging RadarZhi Li0Tian Jin1Yongpeng Dai2Yongkun Song3College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaRadar-based non-contact vital signs monitoring has great value in through-wall detection applications. This paper presents the theoretical and experimental study of through-wall respiration and heartbeat pattern extraction from multiple subjects. To detect the vital signs of multiple subjects, we employ a low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) imaging radar and derive the relationship between radar images and vibrations caused by human cardiopulmonary movements. The derivation indicates that MIMO radar imaging with the stepped-frequency continuous-wave (SFCW) improves the signal-to-noise ratio (SNR) critically by the factor of radar channel number times frequency number compared with continuous-wave (CW) Doppler radars. We also apply the three-dimensional (3-D) higher-order cumulant (HOC) to locate multiple subjects and extract the phase sequence of the radar images as the vital signs signal. To monitor the cardiopulmonary activities, we further exploit the VMD algorithm with a proposed grouping criterion to adaptively separate the respiration and heartbeat patterns. A series of experiments have validated the localization and detection of multiple subjects behind a wall. The VMD algorithm is suitable for separating the weaker heartbeat pattern from the stronger respiration pattern by the grouping criterion. Moreover, the continuous monitoring of heart rate (HR) by the MIMO radar in real scenarios shows a strong consistency with the reference electrocardiogram (ECG).https://www.mdpi.com/2072-4292/13/15/2905multi-subject localizationvital signs detectionrespiration and heartbeat patternsthrough-wall radar imagingVMD |
| spellingShingle | Zhi Li Tian Jin Yongpeng Dai Yongkun Song Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar Remote Sensing multi-subject localization vital signs detection respiration and heartbeat patterns through-wall radar imaging VMD |
| title | Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar |
| title_full | Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar |
| title_fullStr | Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar |
| title_full_unstemmed | Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar |
| title_short | Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar |
| title_sort | through wall multi subject localization and vital signs monitoring using uwb mimo imaging radar |
| topic | multi-subject localization vital signs detection respiration and heartbeat patterns through-wall radar imaging VMD |
| url | https://www.mdpi.com/2072-4292/13/15/2905 |
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