Robust distributed Kalman filter for wireless sensor networks with uncertain communication channels

We address a state estimation problem over a large-scale sensor network with uncertain communication channel. Consensus protocol is usually used to adapt a large-scale sensor network. However, when certain parts of communication channels are broken down, the accuracy performance is seriously degrade...

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Main Authors: Kim, Du Yong, Jeon, M.
Format: Journal Article
Published: Hindawi Publishing Corporation 2012
Online Access:http://hdl.handle.net/20.500.11937/55598
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author Kim, Du Yong
Jeon, M.
author_facet Kim, Du Yong
Jeon, M.
author_sort Kim, Du Yong
building Curtin Institutional Repository
collection Online Access
description We address a state estimation problem over a large-scale sensor network with uncertain communication channel. Consensus protocol is usually used to adapt a large-scale sensor network. However, when certain parts of communication channels are broken down, the accuracy performance is seriously degraded. Specifically, outliers in the channel or temporal disconnection are avoided via proposed method for the practical implementation of the distributed estimation over large-scale sensor networks. We handle this practical challenge by using adaptive channel status estimator and robust L1-norm Kalman filter in design of the processor of the individual sensor node. Then, they are incorporated into the consensus algorithm in order to achieve the robust distributed state estimation. The robust property of the proposed algorithm enables the sensor network to selectively weight sensors of normal conditions so that the filter can be practically useful. Copyright © 2012 Du Yong Kim and Moongu Jeon.
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institution Curtin University Malaysia
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publishDate 2012
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spelling curtin-20.500.11937-555982017-09-27T07:26:32Z Robust distributed Kalman filter for wireless sensor networks with uncertain communication channels Kim, Du Yong Jeon, M. We address a state estimation problem over a large-scale sensor network with uncertain communication channel. Consensus protocol is usually used to adapt a large-scale sensor network. However, when certain parts of communication channels are broken down, the accuracy performance is seriously degraded. Specifically, outliers in the channel or temporal disconnection are avoided via proposed method for the practical implementation of the distributed estimation over large-scale sensor networks. We handle this practical challenge by using adaptive channel status estimator and robust L1-norm Kalman filter in design of the processor of the individual sensor node. Then, they are incorporated into the consensus algorithm in order to achieve the robust distributed state estimation. The robust property of the proposed algorithm enables the sensor network to selectively weight sensors of normal conditions so that the filter can be practically useful. Copyright © 2012 Du Yong Kim and Moongu Jeon. 2012 Journal Article http://hdl.handle.net/20.500.11937/55598 10.1155/2012/238597 http://creativecommons.org/licenses/by/3.0/ Hindawi Publishing Corporation fulltext
spellingShingle Kim, Du Yong
Jeon, M.
Robust distributed Kalman filter for wireless sensor networks with uncertain communication channels
title Robust distributed Kalman filter for wireless sensor networks with uncertain communication channels
title_full Robust distributed Kalman filter for wireless sensor networks with uncertain communication channels
title_fullStr Robust distributed Kalman filter for wireless sensor networks with uncertain communication channels
title_full_unstemmed Robust distributed Kalman filter for wireless sensor networks with uncertain communication channels
title_short Robust distributed Kalman filter for wireless sensor networks with uncertain communication channels
title_sort robust distributed kalman filter for wireless sensor networks with uncertain communication channels
url http://hdl.handle.net/20.500.11937/55598