Through-Wall Bio-Radiolocation With UWB Impulse Radar: Observation, Simulation and Signal Extraction

Liu, Lanbo; Liu, Zijian; Barrowes, Benjamin E.

doi:10.1109/jstars.2011.2157461

Cited by 99 publications

(53 citation statements)

References 11 publications

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“…where d 0 is the distance of the inspected person, B is the amplitude of the chest surface radial motion, normally between 5mm and 15mm [11], f r is the respiratory frequency, normally between 0.2Hz and 0.5Hz, and u is the power of cosine function which must be even. Fig.…”

Section: A Uwb Respiratory Signal Modelmentioning

confidence: 99%

A novel through-wall respiration detection algorithm using UWB radar

Qiao

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Through-wall respiration detection using Ultra-wideband (UWB) impulse radar can be applied to the post-disaster rescue, e.g., searching living persons trapped in ruined buildings after an earthquake. Since strong interference signals always exist in the real-life scenarios, such as static clutter, noise, etc., while the respiratory signal is very weak, the signal to noise and clutter ratio (SNCR) is quite low. Therefore, through-wall respiration detection using UWB impulse radar under low SNCR is a challenging work in the research field of searching survivors after disaster. In this paper, an improved UWB respiratory signal model is built up based on an even power of cosine function for the first time. This model is used to reveal the harmonic structure of respiratory signal, based on which a novel high-performance respiration detection algorithm is proposed. This novel algorithm is assessed by experimental verification and simulation and shows about a 1.5dB improvement of SNR and SNCR.

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Section: A Uwb Respiratory Signal Modelmentioning

confidence: 99%

A novel through-wall respiration detection algorithm using UWB radar

Qiao

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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“…UWB radar also finds application in through-the-wall detection of human subjects, imaging, detection of moving targets, etc. UWB radars for detection of vital signs of a human subject were discussed in [5][6][7][8][9][10]. Signal processing plays a very important role in vital sign detection using Doppler radar.…”

Section: Introductionmentioning

confidence: 99%

“…Signal processing plays a very important role in vital sign detection using Doppler radar. Various algorithms such as parameterized demodulation, singular value decomposition (SVD), adaptive cancellation of clutter, constant false alarm ratio (CFAR) and correlation were proposed to extract vital signs from the received noisy signal [7][8][9][10][11]. But these signal processing algorithms do not separate the vital signs of multiple subjects.…”

Section: Introductionmentioning

confidence: 99%

Through the Wall Respiration Rate Detection of Multiple Human Subjects Using Hilbert Vibrational Decomposition

Harikesh¹,

Basu²,

Abegaonkar³

et al. 2019

PIER M

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In this paper, through-the-wall detection of multiple human subjects is demonstrated using Doppler radar, with the help of Hilbert Vibrational Decomposition (HVD). The proposed Doppler radar can detect multiple human subjects behind a wall by respiration rate estimation. With different breathing conditions resembling real-life scenario, respiration signals of human subjects are extracted. The algorithm works in many real-life situations and detects the respiration rate of human subjects. It is expected to find use in the earthquakes, building collapses and security applications.

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“…UWB waveform provides high range resolution ability, and thus has the potential to determine the distance of humans with high accuracy [11,12]. This allows accurate localization of the breathing subject and tracking of the small movements of the diaphragm during breathing [13]. In [14], UWB impulse radar was used to monitor the breathing rates of two subjects through a cement wall.…”

Section: Introductionmentioning

confidence: 99%

Detection of Multiple Stationary Humans Using UWB MIMO Radar

Liang

et al. 2016

Sensors

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Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls.

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Through-Wall Bio-Radiolocation With UWB Impulse Radar: Observation, Simulation and Signal Extraction

Cited by 99 publications

References 11 publications

A novel through-wall respiration detection algorithm using UWB radar

A novel through-wall respiration detection algorithm using UWB radar

Through the Wall Respiration Rate Detection of Multiple Human Subjects Using Hilbert Vibrational Decomposition

Detection of Multiple Stationary Humans Using UWB MIMO Radar

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