Particle filter for tracking linear Gaussian target with nonlinear observations

Augustine T. Ooi; Arnaud Doucet; Ba-Ngu B. Vo; Branko Ristic

doi:10.1117/12.487496

25 August 2003 Particle filter for tracking linear Gaussian target with nonlinear observations

Augustine T. Ooi, Arnaud Doucet, Ba-Ngu B. Vo, Branko Ristic

Proceedings Volume 5096, Signal Processing, Sensor Fusion, and Target Recognition XII; (2003) https://doi.org/10.1117/12.487496
Event: AeroSense 2003, 2003, Orlando, Florida, United States

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.

Citation Download Citation

Augustine T. Ooi, Arnaud Doucet, Ba-Ngu B. Vo, and Branko Ristic "Particle filter for tracking linear Gaussian target with nonlinear observations", Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); https://doi.org/10.1117/12.487496

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