UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

SimHumalator: An Open Source End-to-End Radar Simulator For Human Activity Recognition

Vishwakarma, S; Li, W; Tang, C; Woodbridge, K; Adve, R; Chetty, K; (2022) SimHumalator: An Open Source End-to-End Radar Simulator For Human Activity Recognition. IEEE Aerospace and Electronic Systems Magazine (In press). Green open access

[thumbnail of SimHumalator_AESS_Magazine_accepted.pdf]
Preview
Text
SimHumalator_AESS_Magazine_accepted.pdf - Accepted Version

Download (4MB) | Preview

Abstract

Radio-frequency based non-cooperative monitor ing of humans has numerous applications ranging from law enforcement to ubiquitous sensing applications such as ambient assisted living and bio-medical applications for non-intrusively monitoring patients. Large training datasets, almost unlimited memory capacity, and ever- increasing processing speeds of computers could drive forward the data- driven deep-learning focused research in the above applications. However, generating and labeling large volumes of high-quality, diverse radar datasets is an onerous task. Furthermore, unlike the fields of vision and image processing, the radar community has limited access to databases that contain large volumes of experimental data. Therefore, in this article, we present an open-source motion capture data-driven simulation tool, SimHumalator, that can generate large volumes of human micro-Doppler radar data in passive WiFi scenarios. The simulator integrates IEEE 802.11 WiFi standard(IEEE 802.11g, n, and ad) compliant transmissions with the human animation data to generate the micro-Doppler features that incorporate the diversity of human motion characteristics and the sensor parameters. The simulated signatures have been validated with experimental data gathered using an in-house-built hardware prototype. This article describes simulation methodology in detail and provides case studies on the feasibility of using simulated micro-Doppler spectrograms for data augmentation tasks.

Type: Article
Title: SimHumalator: An Open Source End-to-End Radar Simulator For Human Activity Recognition
Open access status: An open access version is available from UCL Discovery
Publisher version: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?pu...
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: Passive WiFi Sensing, micro-Doppler, activity recognition, deep learning, simulator
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 Electronic and Electrical Eng
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/10140989
Downloads since deposit
99Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item