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Super-resolution Localization and Tracking in WiFi Sensing

Published

Author(s)

Jian Wang, Jack Chuang, Nada Golmie

Abstract

Integrated sensing and communication (ISAC) systems have been investigated by the research and standardization communities in the recent past. Accurate localizing the target and tracking the target's movement are critical for numerous smart Internet of Things (IoT) systems (smart manufacturing, smart transportation, etc.). This paper aims to realize super-resolution localization and tracking in WiFi sensing by leveraging the IEEE 802.11ad beamforming training procedure. We leverage the CLEAN-Space-Alternating Generalized Expectation-maximization (CLEAN-SAGE) algorithm on a single beam sweeping cycle for target localization and investigate the targets' delays and angle estimation. For tracking moving targets, we design mechanisms to estimate the target's motion, including the target's velocity and motion pattern, such as estimating the target's spatial positions over time to obtain the Doppler shift or tracking its trajectory using the Kalman filter. To validate the efficacy of our approach, we conduct an extensive performance evaluation study. Our evaluation results confirm that the CLEAN-SAGE algorithm can achieve estimation performance beyond the ISAC system's inherent bandwidth and beamwidth constraints. Furthermore, we provide insights into how system configurations, including antenna size, beam overlap, and the number of iterations in the SAGE algorithm, influence the evaluation performance.
Proceedings Title
Proceedings of the 2024 IEEE International Conference on Computer Communications and Networks (ICCCN)
Conference Dates
July 29-31, 2024
Conference Location
Big Island, HI, US

Keywords

Edge processing, IoT applications, mmWave, CLEAN, SAGE, WiFi sensing, super-resolution algorithm, localization, tracking

Citation

Wang, J. , Chuang, J. and Golmie, N. (2024), Super-resolution Localization and Tracking in WiFi Sensing, Proceedings of the 2024 IEEE International Conference on Computer Communications and Networks (ICCCN), Big Island, HI, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=957603 (Accessed April 5, 2025)

Issues

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Created July 29, 2024, Updated April 3, 2025