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Rich probabilistic representations for bearing only decentralised data fusion

Upcroft, Ben, Ong, Lee Ling., Kumar, Suresh, Ridley, Matthew, Bailey, Tim, Sukkarieh, Salah, & Durrant-Whyte, Hugh (2005) Rich probabilistic representations for bearing only decentralised data fusion. In Proceedings 8th International Conference on Information Fusion, 2005, IEEE, Wyndham Philadelphia at Franklin Plaza Philadelphia, PA, USA.

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Abstract

The aim of this paper is to demonstrate the validity of using Gaussian mixture models (GMM) for representing probabilistic distributions in a decentralised data fusion (DDF) framework. GMMs are a powerful and compact stochastic representation allowing efficient communication of feature properties in large scale decentralised sensor networks. It will be shown that GMMs provide a basis for analytical solutions to the update and prediction operations for general Bayesian filtering. Furthermore, a variant on the Covariance Intersect algorithm for Gaussian mixtures will be presented ensuring a conservative update for the fusion of correlated information between two nodes in the network. In addition, purely visual sensory data will be used to show that decentralised data fusion and tracking of non-Gaussian states observed by multiple autonomous vehicles is feasible.

Impact and interest:

5 citations in Scopus
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ID Code: 40433
Item Type: Conference Paper
Keywords: Bayesian filtering, probabilistic distribution, decentralised data fusion framework, covariance intersect algorithm, correlated information, DDF, GMM, Gaussian mixture model, autonomous vehicle, communication feature property, sensor network, stochastic representation, tracking
DOI: 10.1109/ICIF.2005.1591974
ISBN: 0780392868 Print
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright IEEE 2005
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 10 May 2011 11:52
Last Modified: 14 Aug 2011 00:21

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