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The marginalized particle filter – analysis, applications and generalizations
Thomas B. Schön1 ; Rickard Karlsson1 ; Fredrik Gustafsson1
1 Division of Automatic Control, Department of Electrical Engineering, Linköping University, Sweden SE–581 83 Linköping, Sweden
ESAIM. Proceedings, Tome 19 (2007), pp. 53-64 Cet article a éte moissonné depuis la source EDP Sciences

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The marginalized particle filter is a powerful combination of the particle filter and the Kalman filter, which can be used when the underlying model contains a linear sub-structure, subject to Gaussian noise. This paper outlines the marginalized particle filter and very briefly hint at possible generalizations, giving rise to a larger family of marginalized nonlinear filters. Furthermore, we analyze several properties of the marginalized particle filter, including its ability to reduce variance and its computational complexity. Finally, we provide an introduction to various applications of the marginalized particle filter.
DOI : 10.1051/proc:071908

Thomas B. Schön 1 ; Rickard Karlsson 1 ; Fredrik Gustafsson 1

1 Division of Automatic Control, Department of Electrical Engineering, Linköping University, Sweden SE–581 83 Linköping, Sweden 
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     title = {The marginalized particle filter {\textendash} analysis, applications and generalizations},
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Thomas B. Schön; Rickard Karlsson; Fredrik Gustafsson. The marginalized particle filter – analysis, applications and generalizations. ESAIM. Proceedings, Tome 19 (2007), pp. 53-64. doi: 10.1051/proc:071908

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