Position-Information-Indexed Classifier for Improved Through-Wall Detection and Classification of Human Activities Using UWB Bio-Radar

Qi, Fugui; Liang, Fuyuan; Liu, Miao; Lv, Hao; Wang, Pengfei; Xue, Huijun; Wang, Jianqi

doi:10.1109/lawp.2019.2893358

Cited by 37 publications

(12 citation statements)

References 16 publications

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“…n the past decade, Ultra-wideband (UWB) technology has received great attention due to the supported high data rates, the low transmitted power (-44.3 dBm) requirements, and its inherent resistance to jamming and relative immunity to multipath fading [1,2]. Due to these advantages, it has been used in a wide range of different applications such as cognitive radio [3], short-range in-house communications, wireless sensor networks, healthcare and biomedical wireless systems [4], sensing and imaging systems [5], radar detecting and target locating [6] and IoT applications [7,8].…”

Section: Introductionmentioning

confidence: 99%

Dynamically Reconfigurable UWB Antenna Using an FET Switch Powered by Wireless RF Harvested Energy

Quddious

Abbasi

Antoniades

et al. 2020

IEEE Trans. Antennas Propagat.

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A dynamically reconfigurable dual-layer UWB antenna integrated with an energy harvesting system for powering a GaAs FET switch is presented. The UWB antenna dynamically creates a notch-band in the presence of an interfering signal at 5.6 GHz and it goes back to normal UWB operation when the interferer is removed. For the switching operation, the FET switch is powered using only harvested energy carried by the interfering signals. The UWB antenna on the front layer is a microstrip-fed monopole with an embedded elliptical slot. Inside the slot a quarter wavelength linear stub acts as a resonator and it is connected and disconnected using the low-power FET switch. The UWB antenna shares the RF ground with a very compact energy harvesting system, that consists of a planar inverted-F antenna, a very compact voltage doubler rectifier and a passive DC-to-DC boost converter. The boost converter elevates the rectified voltage to above the 3.3 V threshold, which is the minimum voltage needed for the actuation of the FET switch. The dynamic notch-band reconfiguration of the UWB antenna without the need for any external DC power source is made possible when the collected power at the input of the rectifier is higher than -12 dBm.

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Section: Introductionmentioning

confidence: 99%

Dynamically Reconfigurable UWB Antenna Using an FET Switch Powered by Wireless RF Harvested Energy

Quddious

Abbasi

Antoniades

et al. 2020

IEEE Trans. Antennas Propagat.

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“…To associate these parameters over all four domains, it is necessary to determine the most likely index combinations l 12 , l 23 , l 34 , l 41 , where l = l 12 represents a paired index between domains 1 and 2, and l is used as an independent variable hereafter. Because the parameters are already associated for the adjacent domain pairs (1, 2), (2,3), (3,4), and (4, 1), the number of degrees of freedom is three. To optimize the indices l 23 , l 34 , and l 41 for l = l 12 , the evaluation function l (l 23 , l 34 , l 41 ) is introduced as follows:…”

Section: Pairing Eigenvalues In Multidimensional Esprit 1) Overviementioning

confidence: 99%

Accurate Ultra-Wideband Array Radar Imaging Using Four-Dimensional Unitary ESPRIT

Morimoto¹,

Sakamoto

Sato

2019

IEEE Access

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Adaptive signal processing techniques can estimate the directions of arrival (DOAs), ranges, and radial velocities of radar targets with high resolution when applied in the space, frequency, and time domains, respectively. However, the performance of these techniques is limited when they are applied separately in each domain. Recently, adaptive signal processing algorithms based on high-dimensional signal subspaces have been studied extensively. We apply a four-dimensional unitary estimation of signal parameters via rotational invariant techniques (ESPRIT) algorithm for the simultaneous estimation of the DOAs, ranges, and Doppler velocities of multiple targets in an ultra-wideband radar imaging setting and show the effectiveness of the high-dimensional ESPRIT for the near-field imaging of distributed moving targets. The four-dimensional ESPRIT algorithm is demonstrated to be able to separate targets moving in close proximity, whereas the two-and three-dimensional ESPRIT algorithms fail to separate these targets accurately because of their limited resolutions. The application of the high-dimensional ESPRIT to near-field radar imaging covers a wide range of applications that require the measurement of multiple moving targets in close proximity. An example of such an application is radar-based human monitoring. Therefore, the superior resolution of the high-dimensional ESPRIT has the potential to improve the performance of various real-world security and healthcare systems. INDEX TERMS Adaptive signal processing, direction-of-arrival, multidimensional signal processing, radar imaging, ultra wideband radar.

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“…Not only applicable in residency environments, UWB radar is a feasible solution in rescue and other safety related operations, as presented in [ 13 , 22 ]. The dual use of analysis of the received signal can be utilized to observe and locate living persons inside ruins, an avalanche, etc.…”

Section: Introductionmentioning

confidence: 99%

Ultra-Wideband Radar-Based Indoor Activity Monitoring for Elderly Care

Hämäläinen

Mucchi

Caputo

et al. 2021

Sensors

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In this paper, we propose an unobtrusive method and architecture for monitoring a person’s presence and collecting his/her health-related parameters simultaneously in a home environment. The system is based on using a single ultra-wideband (UWB) impulse-radar as a sensing device. Using UWB radars, we aim to recognize a person and some preselected movements without camera-type monitoring. Via the experimental work, we have also demonstrated that, by using a UWB signal, it is possible to detect small chest movements remotely to recognize coughing, for example. In addition, based on statistical data analysis, a person’s posture in a room can be recognized in a steady situation. In addition, we implemented a machine learning technique (k-nearest neighbour) to automatically classify a static posture using UWB radar data. Skewness, kurtosis and received power are used in posture classification during the postprocessing. The classification accuracy achieved is more than 99%. In this paper, we also present reliability and fault tolerance analyses for three kinds of UWB radar network architectures to point out the weakest item in the installation. This information is highly important in the system’s implementation.

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Position-Information-Indexed Classifier for Improved Through-Wall Detection and Classification of Human Activities Using UWB Bio-Radar

Cited by 37 publications

References 16 publications

Dynamically Reconfigurable UWB Antenna Using an FET Switch Powered by Wireless RF Harvested Energy

Dynamically Reconfigurable UWB Antenna Using an FET Switch Powered by Wireless RF Harvested Energy

Accurate Ultra-Wideband Array Radar Imaging Using Four-Dimensional Unitary ESPRIT

Ultra-Wideband Radar-Based Indoor Activity Monitoring for Elderly Care

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