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A Novel Sequential Monte Carlo Approach for Extended Object Tracking Based on Border Parameterisation

Research output: Contribution in Book/Report/ProceedingsPaper

Published

Publication date07/2011
Host publication14th International Conference on Information Fusion: ISIF
Place of publicationChicago, Illinois, USA
Pages306-313
Number of pages8
ISBN (Electronic)978-0-9824438-3-5, IEEE Catalog Number: CFP11FUS-CDR
Original languageEnglish

Abstract

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.