Hybrid Fusion for 802.11ax Wi-Fi-based Passive Radars Exploiting Beamforming Feedbacks
Martin Willame, Hasan Can Yildirim, Laurent Storrer, Francois Horlin, and Jerome Louveaux

TL;DR
This paper proposes a hybrid fusion method for passive Wi-Fi radars that combines information from channel preambles and beamforming feedbacks to improve target localization accuracy.
Contribution
It introduces a novel hybrid fusion approach that leverages both NDP and BFF data, with an optimal maximum likelihood fusion rule for enhanced localization.
Findings
Hybrid fusion improves localization accuracy over classical methods.
BFF-based line-of-sight angle estimation enhances target detection.
Simulation results demonstrate significant performance gains.
Abstract
Passive Wi-Fi-based radars (PWRs) are devices that enable the localization of targets using Wi-Fi signals of opportunity transmitted by an access point. Unlike active radars that optimize their transmitted waveform for localization, PWRs align with the 802.11 amendments. Specifically, during the channel sounding session preceding a multi-user multiple-input multiple-output downlink transmission, an access point isotropically transmits a null data packet (NDP) with a known preamble. From these known symbols, client user equipments derive their channel state information and transmit an unencrypted beamforming feedback (BFF) back to the access point. The BFF comprises the right singular matrix of the channel and the corresponding stream gain for each subcarrier, which allows the computation of a beamforming matrix at the access point. In a classical PWR processing, only the preamble…
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Taxonomy
TopicsRadar Systems and Signal Processing · Ultra-Wideband Communications Technology · Antenna Design and Optimization
MethodsALIGN
