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Mathematical Problems in Engineering
Volume 2012, Article ID 238597, 12 pages
Research Article

Robust Distributed Kalman Filter for Wireless Sensor Networks with Uncertain Communication Channels

School of Information and Communication, Gwangju Institute of Science and Technology, Gwangju 500-712, Republic of Korea

Received 28 November 2011; Revised 11 March 2012; Accepted 30 March 2012

Academic Editor: M. D. S. Aliyu

Copyright © 2012 Du Yong Kim and Moongu Jeon. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.