Experimental Evaluation of a Distributed Kalman Filter Algorithm
Alriksson, Peter LU and Rantzer, Anders LU
(2007)
46th IEEE Conference on Decision and Control, 2007
p.3562-3567
- Abstract
- This paper evaluates the performance of a distributed Kalman filter applied to an ultrasound based positioning application with seven sensor nodes. By distributed we mean that all nodes in the network desires an estimate of the full state of the observed system and there is no centralized computation center after deployment. Communication only takes place between neighbors and only once each sampling interval. The problem is solved by communicating estimates between neighbors and then forming a weighted average as the new estimate. 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. In the experimental setup the... (More)
- This paper evaluates the performance of a distributed Kalman filter applied to an ultrasound based positioning application with seven sensor nodes. By distributed we mean that all nodes in the network desires an estimate of the full state of the observed system and there is no centralized computation center after deployment. Communication only takes place between neighbors and only once each sampling interval. The problem is solved by communicating estimates between neighbors and then forming a weighted average as the new estimate. 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. In the experimental setup the distributed solution performs almost as good as a centralized solution. The proposed algorithm also proved very robust against packet loss. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1021950
- author
- Alriksson, Peter
LU
and Rantzer, Anders
LU
- organization
- publishing date
- 2007
- type
- Contribution to conference
- publication status
- published
- subject
- pages
- 3562 - 3567
- conference name
- 46th IEEE Conference on Decision and Control, 2007
- conference location
- New Orleans, LA, United States
- conference dates
- 2007-12-12 - 2007-12-14
- external identifiers
-
- wos:000255181701284
- scopus:52949083397
- language
- English
- LU publication?
- yes
- id
- cf467e00-0cde-45fe-a29c-bde162237efb (old id 1021950)
- date added to LUP
- 2016-04-04 13:35:23
- date last changed
- 2023-11-16 10:01:20
@misc{cf467e00-0cde-45fe-a29c-bde162237efb,
abstract = {{This paper evaluates the performance of a distributed Kalman filter applied to an ultrasound based positioning application with seven sensor nodes. By distributed we mean that all nodes in the network desires an estimate of the full state of the observed system and there is no centralized computation center after deployment. Communication only takes place between neighbors and only once each sampling interval. The problem is solved by communicating estimates between neighbors and then forming a weighted average as the new estimate. 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. In the experimental setup the distributed solution performs almost as good as a centralized solution. The proposed algorithm also proved very robust against packet loss.}},
author = {{Alriksson, Peter and Rantzer, Anders}},
language = {{eng}},
pages = {{3562--3567}},
title = {{Experimental Evaluation of a Distributed Kalman Filter Algorithm}},
url = {{https://lup.lub.lu.se/search/files/6157298/8411764.pdf}},
year = {{2007}},
}