Petrov, Nikolay and Mihaylova, Lyudmila and Gning, Amadou and Angelova, Donka (2011) A Novel Sequential Monte Carlo Approach for Extended Object Tracking Based on Border Parameterisation. In: 14th International Conference on Information Fusion : ISIF. , Chicago, Illinois, USA, pp. 306-313. ISBN 978-0-9824438-3-5Full text not available from this repository.
Extended objects are characterised with multiple measurements originated from different locations of the object surface. This paper presents a novel Sequential Monte Carlo (SMC) approach for extended object tracking based on border parametrisation. The problem is formulated for general nonlinear problems. The main contribution of this work is in the derivation of the likelihood function for nonlinear measurement functions, with sets of measurements belonging to a bounded region. Simulation results are presented when the object is surrounded by a circular region. Accurate estimation results are presented both for the object kinematic state and object extent.
|Item Type:||Contribution in Book/Report/Proceedings|
|Uncontrolled Keywords:||sequential Monte Carlo methods ; measurement uncertainty ; nonlinear estimation|
|Departments:||Faculty of Science and Technology > School of Computing & Communications|
|Deposited On:||17 May 2012 16:56|
|Last Modified:||30 Apr 2017 01:56|
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