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UWB and WiFi Systems as Passive Opportunistic Activity Sensing Radars

Bocus, MJ; Chetty, K; Piechocki, RJ; (2021) UWB and WiFi Systems as Passive Opportunistic Activity Sensing Radars. In: Proceedings of the 2021 IEEE Radar Conference (RadarConf21). IEEE: Atlanta, GA, USA. Green open access

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Abstract

Human Activity Recognition (HAR) is becoming increasingly important in smart homes and healthcare applications such as assisted-living and remote health monitoring. In this paper, we use Ultra-Wideband (UWB) and commodity WiFi systems for the passive sensing of human activities. These systems are based on a receiver-only radar network that detects reflections of ambient Radio-Frequency (RF) signals from humans in the form of Channel Impulse Response (CIR) and Channel State Information (CSI). An experiment was performed whereby the transmitter and receiver were separated by a fixed distance in a Line-of-Sight (LoS) setting. Five activities were performed in between them, namely, sitting, standing, lying down, standing from the floor and walking. We use the high-resolution CIRs provided by the UWB modules as features in machine and deep learning algorithms for classifying the activities. Experimental results show that a classification performance with an F1-score as high as 95.53% is achieved using processed UWB CIR data as features. Furthermore, we analysed the classification performance in the same physical layout using CSI data extracted from a dedicated WiFi Network Interface Card (NIC). In this case, maximum F1-scores of 92.24% and 80.89% are obtained when amplitude CSI data and spectrograms are used as features, respectively.

Type: Proceedings paper
Title: UWB and WiFi Systems as Passive Opportunistic Activity Sensing Radars
Event: 2021 IEEE Radar Conference (RadarConf21)
Location: IEEE Atlanta Sect, ELECTR NETWORK
Dates: 08 May 2021 - 14 May 2021
ISBN-13: 978-1-7281-7609-3
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/RadarConf2147009.2021.9455175
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Legged locomotion, Passive radar, Signal processing algorithms, Smart homes, Sensors, Classification algorithms, Ultra wideband radar
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery.ucl.ac.uk/id/eprint/10134704
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