IEEE 802.11bf Multistatic Sensing with Unsynchronized Receivers

Distinct from existing works on millimeter wave Wi-Fi sensing in a monostatic or bistatic setting, in this paper we present a complete framework for multistatic sensing with unsynchronized receivers using IEEE 802.11bf signals. Based on the channel estimates from the active sensing procedure, each receiver extracts the line-of-sight and the target-reflected paths, and reports the time-difference-of-arrivals to a central server, which localizes and potentially tracks the target. We simulate the system using the QD channel simulator and the ISAC-PLM software package from NIST, and present the measurement accuracy at each receiver and the localization accuracy at the central server. Numerical results show promising localization performance at reasonable signal-to-noise ratio (SNR) levels.

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Publication Details

Published
2025-06-08
DOI
https://doi.org/10.1109/ssp64130.2025.11073500
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
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article

IEEE 802.11bf Multistatic Sensing with Unsynchronized Receivers

Amir Abdallah, Shengli Zhou, Pu Perry Wang
Indoor and Outdoor Localization Technologies
article

IEEE 802.11bf Multistatic Sensing with Unsynchronized Receivers

Amir Abdallah, Shengli Zhou, Pu Perry Wang
article en

Abstract

Distinct from existing works on millimeter wave Wi-Fi sensing in a monostatic or bistatic setting, in this paper we present a complete framework for multistatic sensing with unsynchronized receivers using IEEE 802.11bf signals. Based on the channel estimates from the active sensing procedure, each receiver extracts the line-of-sight and the target-reflected paths, and reports the time-difference-of-arrivals to a central server, which localizes and potentially tracks the target. We simulate the system using the QD channel simulator and the ISAC-PLM software package from NIST, and present the measurement accuracy at each receiver and the localization accuracy at the central server. Numerical results show promising localization performance at reasonable signal-to-noise ratio (SNR) levels.

University of Connecticut (US), Mitsubishi Electric (United States) (US)
Affordable and clean energy
Openalex Percentile: Top 82%
Indoor and Outdoor Localization Technologies
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