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The Rao-Blackwellized Particle Filter: A Filter Bank Implementation

Gustaf Hendeby; Rickard Karlsson; Fredrik Gustafsson
In: EURASIP Journal on Advances in Signal Processing (ASP), Vol. 2010, No. 724087, Hindawi Publishing Corporation, 2010.

Abstract

For computational efficiency, it is important to utilize model structure in particle filtering. One of the most important cases occurs when there exists a linear Gaussian substructure, which can be efficiently handled by Kalman filters. This is the standard formulation of the Rao-Blackwellized particle filter (RBPF). This contribution suggests an alternative formulation of this well-known result that facilitates reuse of standard filtering components and which is also suitable for object-oriented programming. Our RBPF formulation can be seen as a Kalman filter bank with stochastic branching and pruning.

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