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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)
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author
organization
publishing date
type
Contribution to conference
publication status
published
subject
pages
3562 - 3567
conference name
46th IEEE Conference on Decision and Control, 2007
external identifiers
  • wos:000255181701284
  • scopus:52949083397
language
English
LU publication?
yes
id
cf467e00-0cde-45fe-a29c-bde162237efb (old id 1021950)
date added to LUP
2008-01-31 09:47:24
date last changed
2017-03-19 04:29:07
@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},
  year         = {2007},
}