NDLI: A multi-path data exclusion model for RSSI-based indoor localization

Content Provider	IEEE Xplore Digital Library
Author	Dieng, N.A. Charbit, M. Chaudet, C. Toutain, L. Ben Meriem, T.
Copyright Year	2012
Description	Author affiliation: Institut Mines-Télécom/Télécom ParisTech/CNRS LTCI UMR 5141 - Paris, France (Dieng, N.A.; Charbit, M.; Chaudet, C.) \|\| Institut Mines-Télécom/Télécom Bretagne - Université Européenne de Bretagne - Brest, France (Toutain, L.) \|\| Orange Lab Network Carrier/R&D - Issy-les-Moulineaux, France (Ben Meriem, T.)
Abstract	Positioning a device with the only help of an RF transmitter in an indoor environment is difficult because of the complexity and of the unpredictable nature of radio propagation in such a scenario. The effects of fading, multipath, shadowing make it difficult to infer distance between two points from a blind measurement of the signal attenuation. However, the Received Signal Strength Indicator (RSSI) remains a popular ranging technique when it comes to the Internet of Things, as it does not require dedicated or expensive hardware. The variability of the RSSI is often addressed by modeling channel attenuation by a parametric model like the log-normal shadowing. Such model parameters are generally evaluated by maximum likelihood estimation (MLE). In this paper, we confront this technique to an indoor realistic testbed and show that it achieves a low accuracy. We propose to use an alternate model named biased log-normal shadowing model that is able to alleviate the effects of multipath and show that MLE on this biased model achieves a better precision.
Starting Page	336
Ending Page	340
File Size	179343
Page Count	5
File Format	PDF
ISBN	9781467345330
ISSN	18825621
e-ISBN	9789860334074
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-24
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	NiCT
Subject Keyword	Maximum likelihood estimation RSSI Accuracy IEEE 802.15 Standards Log-normal Shadowing Databases Receivers Mobile communication Experimentation Indoor Localization Shadow mapping
Content Type	Text
Resource Type	Article

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