Updates in Bayesian Filtering by Continuous Projections on a Manifold of Densities

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openAccess
Journal Title
Journal ISSN
Volume Title
Conference article in proceedings
Date
2019-05-01
Major/Subject
Mcode
Degree programme
Language
en
Pages
5
5032-5036
Series
2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Volume 2019-May
Abstract
In this paper, we develop a novel method for approximate continuous-discrete Bayesian filtering. The projection filtering framework is exploited to develop accurate approximations of posterior distributions within parametric classes of probability distributions. This is done by formulating an ordinary differential equation for the posterior distribution that has the prior as initial value and hits the exact posterior after a unit of time. Particular emphasis is put on exponential families, especially the Gaussian family of densities. Experimental results demonstrate the efficacy and flexibility of the method.
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Keywords
Bayesian state estimation, continuous-discrete filtering, non-linear filtering, Projection filtering
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Citation
Tronarp , F & Sarkka , S 2019 , Updates in Bayesian Filtering by Continuous Projections on a Manifold of Densities . in 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019; Brighton; United Kingdom; 12-17 May 2019 : Proceedings . , 8682279 , Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing , vol. 2019-May , IEEE , pp. 5032-5036 , IEEE International Conference on Acoustics, Speech, and Signal Processing , Brighton , United Kingdom , 12/05/2019 . https://doi.org/10.1109/ICASSP.2019.8682279