Principal component analysis of CSI for the robust wireless detection of passive targets

Abstract : Recent standards for wireless networks introduced spatial and frequency diversity to improve the quality and the bandwidth of the wireless communications. The arising channel state information has been exploited for the wireless localization of device-free targets. In this work, a principal component analysis has been applied to the channel state information in order to extract a target-dependent feature suitable to enable the robust detection of passive targets in large indoor areas. The experimental validation performed with commercial WiFi access points pointed out a failure rate lower than 3 [%] in a real indoor test field.
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https://hal.archives-ouvertes.fr/hal-01584113
Contributor : Andrea Massa <>
Submitted on : Friday, September 8, 2017 - 12:35:48 PM
Last modification on : Thursday, April 5, 2018 - 12:30:05 PM

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Federico Viani, Alessandro Polo, Enrico Giarola, Marco Salucci, Andrea Massa. Principal component analysis of CSI for the robust wireless detection of passive targets. International Applied Computational Electromagnetics Society Symposium - Italy (ACES), 2017 , Mar 2017, Florence, Italy. pp.1-2, ⟨10.23919/ROPACES.2017.7916325⟩. ⟨hal-01584113⟩

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