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
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:
https://lup.lub.lu.se/record/3737364
- author
- Berntorp, Karl
LU
; Robertsson, Anders
LU
and Årzén, Karl-Erik
LU
- organization
- publishing date
- 2013
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- [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
- conference location
- Istanbul, Turkey
- conference dates
- 2013-07-09 - 2013-07-12
- 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
- 2016-04-04 10:27:30
- date last changed
- 2022-01-29 20:20:46
@inproceedings{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}},
booktitle = {{[Host publication title missing]}},
language = {{eng}},
pages = {{805--812}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Rao-Blackwellized Out-of-Sequence Processing for Mixed Linear/Nonlinear State-Space Models}},
url = {{https://lup.lub.lu.se/search/files/5543719/3920698.pdf}},
year = {{2013}},
}