NDLI: Multisensor data fusion in the frame of the TBM on reals. Application to land vehicle positioning

Content Provider	IEEE Xplore Digital Library
Author	Caron, F. Smets, P. Duflos, E. Vanheeghe, P.
Copyright Year	2005
Description	Author affiliation: Ecole Centrale de Lille, LAGIS UMAR-CNRS, Villeneuve d'Ascq, France (Caron, F.)
Abstract	This article presents the theoretical foundations of a multisensor data fusion system for land vehicle positioning in the framework of the transferable belief model (TBM) applied on reals. Based on this model and using credal inference, a method similar to Fisher's fiducial inference, each source of information produces some belief on the parameter of interest. Sources are data from sensors, to which observation and evolution models are associated. Still sensor failures may occur and the evolution model can be inappropriate in some extremes situations. Conflicts between the individual inferred beliefs are essential data to be taken into account in a multisensor data fusion system. From these conflicts, explicitly given in the TBM, the beliefs produced by each sensor and the a priori information are weighted by discounting coefficients. Furthermore, sensors data are not necessarily precise, they can be imprecise interval-valued. This provides a better representation in case of imprecision. The TBM gives then a frame to deal with imprecision of data modelled in such a way.
File Size	4064559
File Format	PDF
ISBN	0780392868
DOI	10.1109/ICIF.2005.1592029
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Land vehicles Global Positioning System Information resources Defense industry Accelerometers Gyroscopes Uncertainty Data analysis Multi-sensor Data Fusion Credal inference Transferable Belief Model GPS
Content Type	Text
Resource Type	Article

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