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People Flow Estimation with a Wi-Fi-Based Passive radar

par Storrer, Laurent ;Cakoni, Dejvi ;Yildirim, Hasan Can ;Willame, Martin;Louveaux, Jérôme;De Doncker, Philippe ;Pollin, Sofie;Horlin, François
Référence 4th IEEE International Symposium on Joint Communications & Sensing (JC&S24)(19-21 March, 2024: Leuven, Belgium), Proc. of the 4th IEEE International Symposium on Joint Communications & Sensing (JC&S24)
Publication A Paraître, 2024-03-19

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Résumé :

We investigate crowd monitoring with a Wi-Fi-based passive radar in the context of large events with multiple areas connected by alleys or streets, such as events in city centres. We derive an average people flow expression in people per second, away from a radar and towards it, and propose aprocessing scheme to estimate this flow with a Wi-Fi-based passive radar. It relies on splitting the range-Doppler map (RDM) in its negative and positive Doppler speeds parts, corresponding to the flow away from the radar and towards it respectively, and combining people counting and average people’s speed estimation on each RDM part. A flow estimation error metric is introduced, and our proposed flow estimation framework isexperimentally validated with a Wi-Fi-based passive radar setup using High-Efficiency Long Training Fields from the 802.11ax standard and built with Universal Software Radio Peripherals. A successful flow estimation is achieved, by obtaining a flow estimation error significantly lower than the true flow averaged on all measurements.