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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2012-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2012/238597 |
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doaj-0dfa00094a4f403a9e9bca11e83edbe92020-11-25T01:06:24ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/238597238597Robust Distributed Kalman Filter for Wireless Sensor Networks with Uncertain Communication ChannelsDu Yong Kim0Moongu Jeon1School of Information and Communication, Gwangju Institute of Science and Technology, Gwangju 500-712, Republic of KoreaSchool of Information and Communication, Gwangju Institute of Science and Technology, Gwangju 500-712, Republic of KoreaWe 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.http://dx.doi.org/10.1155/2012/238597 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Du Yong Kim Moongu Jeon |
spellingShingle |
Du Yong Kim Moongu Jeon Robust Distributed Kalman Filter for Wireless Sensor Networks with Uncertain Communication Channels Mathematical Problems in Engineering |
author_facet |
Du Yong Kim Moongu Jeon |
author_sort |
Du Yong Kim |
title |
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_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_sort |
robust distributed kalman filter for wireless sensor networks with uncertain communication channels |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2012-01-01 |
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. |
url |
http://dx.doi.org/10.1155/2012/238597 |
work_keys_str_mv |
AT duyongkim robustdistributedkalmanfilterforwirelesssensornetworkswithuncertaincommunicationchannels AT moongujeon robustdistributedkalmanfilterforwirelesssensornetworkswithuncertaincommunicationchannels |
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1725190416718888960 |