Multi-target human sensing via UWB bio-radar based on multiple antennas

Lv, Hao; Liu, Miao; Jiao, Teng; Zhang, Yang; Yu, Xiao; Sheng, L.; Jing, Xijing; Wang, Jianqi

doi:10.1109/tencon.2013.6718817

Cited by 27 publications

(21 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The radar was custom-made by the Fourth Military Medical University originally for multi-target human sensing or location [11]. In this paper, it was used for the improved detection of human respiration.…”

Section: The Multistatic Uwb Radarmentioning

confidence: 99%

“…In recent years, remote sensing of human targets with ultra-wideband (UWB) radar has attracted increasing attention [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. Since electromagnetic waves transmitted by UWB radar can penetrate through obstacles, such as clothes, walls, building ruins, etc., this technology can be applied in many areas, like medicine, public security, emergence rescue, and so on [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improved Detection of Human Respiration Using Data Fusion Basedon a Multistatic UWB Radar

Yang

et al. 2016

Remote Sensing

Self Cite

View full text Add to dashboard Cite

This paper investigated the feasibility for improved detection of human respiration using data fusion based on a multistatic ultra-wideband (UWB) radar. UWB-radar-based respiration detection is an emerging technology that has great promise in practice. It can be applied to remotely sense the presence of a human target for through-wall surveillance, post-earthquake search and rescue, etc. In these applications, a human target's position and posture are not known a priori. Uncertainty of the two factors results in a body orientation issue of UWB radar, namely the human target's thorax is not always facing the radar. Thus, the radial component of the thorax motion due to respiration decreases and the respiratory motion response contained in UWB radar echoes is too weak to be detected. To cope with the issue, this paper used multisensory information provided by the multistatic UWB radar, which took the form of impulse radios and comprised one transmitting and four separated receiving antennas. An adaptive Kalman filtering algorithm was then designed to fuse the UWB echo data from all the receiving channels to detect the respiratory-motion response contained in those data. In the experiment, a volunteer's respiration was correctly detected when he curled upon a camp bed behind a brick wall. Under the same scenario, the volunteer's respiration was detected based on the radar's single transmitting-receiving channels without data fusion using conventional algorithm, such as adaptive line enhancer and single-channel Kalman filtering. Moreover, performance of the data fusion algorithm was experimentally investigated with different channel combinations and antenna deployments. The experimental results show that the body orientation issue for human respiration detection via UWB radar can be dealt well with the multistatic UWB radar and the Kalman-filter-based data fusion, which can be applied to improve performance of UWB radar in real applications.

show abstract

Section: The Multistatic Uwb Radarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved Detection of Human Respiration Using Data Fusion Basedon a Multistatic UWB Radar

Yang

et al. 2016

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Promising approaches currently include camera based approaches [27], where is usually easier to perform (in comparison other types of sensors) because of the ability to actually view people. Ultra-wideband radars have also been proposed as a potential solution to the people counting problem [28]. Although the above-mentioned approaches have been proposed, it is still a real challenge to count people in a room accurately.…”

Section: A Passive Infrared Sensors Ultrasonic Sensors and People Cmentioning

confidence: 99%

A Web-Based Office Climate Control System Using Wireless Sensors

et al. 2016

View full text Add to dashboard Cite

Abstract-Conventional heating, ventilating, and air conditioning (HVAC) systems usually achieve the desired control level by means of simple ON-OFF control, which can often result in high energy wastage. A potential solution to this issue is intelligent self-regulating HVAC controllers, which base their actions/decisions on sensor data. In this paper, an office climate monitoring and control system is designed and implemented. The system consists of various wireless sensor nodes and a control node. The sensor nodes provide the sensor data necessary to determine occupancy and the control node executes the algorithm, which decides whether to activate cooling or heating based on the sensor data. This system can serve as a controller and can be integrated into HVAC systems in smart buildings. It is shown that the developed control algorithm executed on the control node results in an improvement of up to 39% in energy efficiency over conventional ON-OFF controllers for HVAC systems.

show abstract

“…Cross-correlation is a standard method of estimating the degree of correlation between two series. Some studies have reported the application of cross-correlation for human detection [24,25]. In [24], two identical microwave systems are applied to receive echoes simultaneously and the results after a cross-correlation analysis between the signals from the two receivers show that the noises are suppressed, whereas, the energies of the vital signs of life are accumulated because the signals are correlated and the noises are uncorrelated.…”

Section: Introductionmentioning

confidence: 99%

“…The signal-to-noise ratio is improved. In [25], based on the assumption that the respiration of a target detected from different channels are highly correlated, and the correlation between the respiration of different targets and the noises are low among the channels, a correlation analysis is used to restrain the noises and distinguish the human targets. All the above correlation processing has been done between the radar echoes from different channels; however, correlation analysis between signals from a single channel have not yet been reported.…”

Section: Introductionmentioning

confidence: 99%

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

Zhang

Chen

Xue

et al. 2016

Sensors

Self Cite

View full text Add to dashboard Cite

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

show abstract

Multi-target human sensing via UWB bio-radar based on multiple antennas

Cited by 27 publications

References 19 publications

Improved Detection of Human Respiration Using Data Fusion Basedon a Multistatic UWB Radar

Improved Detection of Human Respiration Using Data Fusion Basedon a Multistatic UWB Radar

A Web-Based Office Climate Control System Using Wireless Sensors

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

Contact Info

Product

Resources

About