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EURASIP Journal on Advances in Signal Processing

, 2010:724087

First Online: 06 December 2010Received: 07 June 2010Revised: 06 September 2010Accepted: 25 November 2010


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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Autor: Gustaf Hendeby - Rickard Karlsson - Fredrik Gustafsson EURASIPMember


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