Distributed Kalman Filtering Using Weighted Averaging
Alriksson, Peter LU and Rantzer, Anders LU
(2006)
17th International Symposium on Mathematical Theory of Networks and Systems, 2006
- Abstract
- This paper addresses the problem of distributed Kalman filtering, with
focus on limiting the required communication bandwidth.
By distributed we refer to a scenario when all nodes in the network desire an
estimate of the full state of the observed system and there is no
centralized computation center. Communication only takes place
between neighbors and only a fixed number of times each sample. To
reduce bandwidth requirements of individual nodes, estimates
instead of measurements are communicated. A new estimate is
then formed as a weighted average of the neighbouring estimates. The
weights are optimized to yield a small estimation error covariance... (More) - This paper addresses the problem of distributed Kalman filtering, with
focus on limiting the required communication bandwidth.
By distributed we refer to a scenario when all nodes in the network desire an
estimate of the full state of the observed system and there is no
centralized computation center. Communication only takes place
between neighbors and only a fixed number of times each sample. To
reduce bandwidth requirements of individual nodes, estimates
instead of measurements are communicated. A new estimate is
then formed as a weighted average of the neighbouring estimates. The
weights are optimized to yield a small estimation error covariance in
stationarity. The minimization can be done off line thus allowing
only estimates to be communicated. The advantage of communicating
estimates instead of measurements becomes more evident when the number
of nodes exceeds the size of the state vector to be estimated. The
algorithm is applied to one
simple second order system and temperature sensing network. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/930205
- author
- Alriksson, Peter
LU
and Rantzer, Anders
LU
- organization
- publishing date
- 2006
- type
- Contribution to conference
- publication status
- published
- subject
- conference name
- 17th International Symposium on Mathematical Theory of Networks and Systems, 2006
- conference location
- Kyoto, Japan
- conference dates
- 2006-07-24 - 2006-07-28
- language
- English
- LU publication?
- yes
- id
- 02021ade-8ae7-4cfe-91be-0eb63bb0d4c9 (old id 930205)
- date added to LUP
- 2016-04-04 14:22:38
- date last changed
- 2018-11-21 21:19:59
@misc{02021ade-8ae7-4cfe-91be-0eb63bb0d4c9,
abstract = {{This paper addresses the problem of distributed Kalman filtering, with<br/><br>
focus on limiting the required communication bandwidth.<br/><br>
By distributed we refer to a scenario when all nodes in the network desire an<br/><br>
estimate of the full state of the observed system and there is no<br/><br>
centralized computation center. Communication only takes place<br/><br>
between neighbors and only a fixed number of times each sample. To<br/><br>
reduce bandwidth requirements of individual nodes, estimates<br/><br>
instead of measurements are communicated. A new estimate is<br/><br>
then formed as a weighted average of the neighbouring estimates. The<br/><br>
weights are optimized to yield a small estimation error covariance in<br/><br>
stationarity. The minimization can be done off line thus allowing<br/><br>
only estimates to be communicated. The advantage of communicating<br/><br>
estimates instead of measurements becomes more evident when the number<br/><br>
of nodes exceeds the size of the state vector to be estimated. The<br/><br>
algorithm is applied to one<br/><br>
simple second order system and temperature sensing network.}},
author = {{Alriksson, Peter and Rantzer, Anders}},
language = {{eng}},
title = {{Distributed Kalman Filtering Using Weighted Averaging}},
url = {{https://lup.lub.lu.se/search/files/6346346/8865321.pdf}},
year = {{2006}},
}