NDLI: Dirichlet Process Mixtures for Density Estimation in Dynamic Nonlinear Modeling: Application to GPS Positioning in Urban Canyons

Content Provider	IEEE Xplore Digital Library
Author	Rabaoui, A. Viandier, N. Duflos, E. Marais, J. Vanheeghe, P.
Copyright Year	1991
Abstract	In global positioning systems (GPS), classical localization algorithms assume, when the signal is received from the satellite in line-of-sight (LOS) environment, that the pseudorange error distribution is Gaussian. Such assumption is in some way very restrictive since a random error in the pseudorange measure with an unknown distribution form is always induced in constrained environments especially in urban canyons due to multipath/masking effects. In order to ensure high accuracy positioning, a good estimation of the observation error in these cases is required. To address this, an attractive flexible Bayesian nonparametric noise model based on Dirichlet process mixtures (DPM) is introduced. Since the considered positioning problem involves elements of non-Gaussianity and nonlinearity and besides, it should be processed on-line, the suitability of the proposed modeling scheme in a joint state/parameter estimation problem is handled by an efficient Rao-Blackwellized particle filter (RBPF). Our approach is illustrated on a data analysis task dealing with joint estimation of vehicles positions and pseudorange errors in a global navigation satellite system (GNSS)-based localization context where the GPS information may be inaccurate because of hard reception conditions.
Sponsorship	IEEE Signal Processing Society
Starting Page	1638
Ending Page	1655
Page Count	18
File Size	3621739
File Format	PDF
ISSN	1053587X
Volume Number	60
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Estimation Bayesian methods Noise Global Positioning System Satellites Receivers Sensors urban canyon Density estimation global navigation satellite system (GNSS) global positioning systems (GPS) nonparametric Bayesian methods pseudorange errors Rao-Blackwellized particle filter (RBPF) sequential Monte Carlo methods
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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