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Distributed Receding Horizon Kalman Filter

Torreblanca, Pepe Maestre; Giselsson, Pontus LU and Rantzer, Anders LU (2010) 49th IEEE Conference on Decision and Control In 49th IEEE Conference on Decision and Control (CDC)
Abstract
In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the agents by means of dual decomposition. The techniques presented in the paper are applied to estimate the position of mobile agents.
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
49th IEEE Conference on Decision and Control (CDC)
conference name
49th IEEE Conference on Decision and Control
external identifiers
  • scopus:79953129243
ISBN
978-1-4244-7745-6
DOI
10.1109/CDC.2010.5717370
language
English
LU publication?
yes
id
68ead8f4-65ef-46c3-832e-51f61ab7e2c9 (old id 8516641)
date added to LUP
2011-02-22 10:03:00
date last changed
2017-07-02 04:47:33
@inproceedings{68ead8f4-65ef-46c3-832e-51f61ab7e2c9,
  abstract     = {In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the agents by means of dual decomposition. The techniques presented in the paper are applied to estimate the position of mobile agents.},
  author       = {Torreblanca, Pepe Maestre and Giselsson, Pontus and Rantzer, Anders},
  booktitle    = {49th IEEE Conference on Decision and Control (CDC) },
  isbn         = {978-1-4244-7745-6 },
  language     = {eng},
  title        = {Distributed Receding Horizon Kalman Filter},
  url          = {http://dx.doi.org/10.1109/CDC.2010.5717370},
  year         = {2010},
}