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Rao-Blackwellized Out-of-Sequence Processing for Mixed Linear/Nonlinear State-Space Models

Berntorp, Karl LU ; Robertsson, Anders LU and Årzén, Karl-Erik LU (2013) 16th International Conference on Information Fusion, 2013 In [Host publication title missing] p.805-812
Abstract
We investigate the out-of-sequence measurements particle filtering problem for a set of conditionally linear Gaussian state-space models, known as mixed linear/nonlinear state-space models. Two different algorithms are proposed, which both exploit the conditionally linear substructure. The first approach is based on storing only a subset of the particles and their weights, which implies low memory and computation requirements. The second approach is based on a recently reported Rao-Blackwellized forward filter/backward simulator, adapted to the out-of-sequence filtering task with computational considerations for enabling online implementations. Simulation studies on two examples show that both approaches outperform recently reported... (More)
We investigate the out-of-sequence measurements particle filtering problem for a set of conditionally linear Gaussian state-space models, known as mixed linear/nonlinear state-space models. Two different algorithms are proposed, which both exploit the conditionally linear substructure. The first approach is based on storing only a subset of the particles and their weights, which implies low memory and computation requirements. The second approach is based on a recently reported Rao-Blackwellized forward filter/backward simulator, adapted to the out-of-sequence filtering task with computational considerations for enabling online implementations. Simulation studies on two examples show that both approaches outperform recently reported particle filters, with the second approach being superior in terms of tracking performance. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
[Host publication title missing]
pages
805 - 812
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
16th International Conference on Information Fusion, 2013
external identifiers
  • WOS:000341370000107
  • Scopus:84890831606
project
ENGROSS
language
English
LU publication?
yes
id
47a0294a-b0ce-4dd8-8da0-12677fda1915 (old id 3737364)
date added to LUP
2013-05-15 09:35:21
date last changed
2016-10-13 04:40:09
@misc{47a0294a-b0ce-4dd8-8da0-12677fda1915,
  abstract     = {We investigate the out-of-sequence measurements particle filtering problem for a set of conditionally linear Gaussian state-space models, known as mixed linear/nonlinear state-space models. Two different algorithms are proposed, which both exploit the conditionally linear substructure. The first approach is based on storing only a subset of the particles and their weights, which implies low memory and computation requirements. The second approach is based on a recently reported Rao-Blackwellized forward filter/backward simulator, adapted to the out-of-sequence filtering task with computational considerations for enabling online implementations. Simulation studies on two examples show that both approaches outperform recently reported particle filters, with the second approach being superior in terms of tracking performance.},
  author       = {Berntorp, Karl and Robertsson, Anders and Årzén, Karl-Erik},
  language     = {eng},
  pages        = {805--812},
  publisher    = {ARRAY(0x7b3b598)},
  series       = {[Host publication title missing]},
  title        = {Rao-Blackwellized Out-of-Sequence Processing for Mixed Linear/Nonlinear State-Space Models},
  year         = {2013},
}