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Rao-Blackwellized Auxiliary Particle Filters for Mixed Linear/Nonlinear Gaussian models

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Author

  • Jerker Nordh

Summary, in English

The Auxiliary Particle Filter is a variant of the common particle filter which attempts to incorporate information from the next measurement to improve the proposal distribution in the update step. This paper studies how this can be done for Mixed Linear/Nonlinear Gaussian models, it builds on a previously suggested method and introduces two new variants which tries to improve the performance by using a more detailed approximation of the true probability density function when evaluating the so called first stage weights. These algorithms are compared for a couple of models to illustrate their strengths and

weaknesses.

Publishing year

2014

Language

English

Pages

1-6

Publication/Series

[Host publication title missing]

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Control Engineering

Conference name

12th International Conference on Signal Processing

Conference date

2014-10-20

Conference place

Hangzhou, China

Status

Published

Research group

  • LCCC
  • ELLIIT

ISBN/ISSN/Other

  • ISSN: 2164-5221