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Proceedings Paper

Particle filter for tracking linear Gaussian target with nonlinear observations
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Paper Abstract

In this paper, a solution to the TENET nonlinear filtering challenge is presented. The proposed approach is based on particle filtering techniques. Particle methods have already been used in this context but our method improves over previous work in several ways: better importance sampling distribution, variance reduction through Rao-Blackwellisation etc. We demonstrate the efficiency of our algorithm through simulation.

Paper Details

Date Published: 25 August 2003
PDF: 12 pages
Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); doi: 10.1117/12.487496
Show Author Affiliations
Augustine T. Ooi, Univ. of Melbourne (Australia)
Arnaud Doucet, Univ. of Cambridge (United Kingdom)
Ba-Ngu B. Vo, Univ. of Melbourne (Australia)
Branko Ristic, Defence Science and Technology Organisation (Australia)

Published in SPIE Proceedings Vol. 5096:
Signal Processing, Sensor Fusion, and Target Recognition XII
Ivan Kadar, Editor(s)

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