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Communication Dans Un Congrès Année : 2011

Fingerprinting localization based on neural networks and ultra-wideband signals

Résumé

Fingerprinting techniques have been proved as an effective techniques for determining the position of a mobile user in an indoor environment and in challenging environments such as mines, canyons, and tunnels where common localization techniques based on time of arrival (TOA) or received signal strength (RSS) are subject to big positioning errors. In this paper, a fingerprinting based localization technique using neural networks and ultra-wideband signals (UWB) is presented as an alternative. The fingerprinting database is built with signatures extracted from channel impulse responses (CIR) obtained by processing an IR-UWB indoor propagation measurement campaign. The construction of the neural networks and the adopted approach are described. Positioning performances are evaluated with different selected signatures and different sizes of the fingerprinting database.
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Dates et versions

hal-00684401 , version 1 (02-04-2012)

Identifiants

Citer

Lei Yu, Mohamed Laaraiedh, Stephane Avrillon, Bernard Uguen. Fingerprinting localization based on neural networks and ultra-wideband signals. Signal Processing and Information Technology (ISSPIT), 2011 IEEE International Symposium on, Dec 2011, Bilbao, Spain. pp.184 -189, ⟨10.1109/ISSPIT.2011.6151557⟩. ⟨hal-00684401⟩
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