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Journal of Applied Mathematics
Volume 2013, Article ID 683249, 9 pages
Research Article

Distributed Filter with Consensus Strategies for Sensor Networks

Faculty of Information, Zhejiang University, Hangzhou 310027, China

Received 12 August 2013; Accepted 28 August 2013

Academic Editor: Baocang Ding

Copyright © 2013 Xie Li et al. 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.


Consensus algorithm for networked dynamic systems is an important research problem for data fusion in sensor networks. In this paper, the distributed filter with consensus strategies known as Kalman consensus filter and information consensus filter is investigated for state estimation of distributed sensor networks. Firstly, an in-depth comparison analysis between Kalman consensus filter and information consensus filter is given, and the result shows that the information consensus filter performs better than the Kalman consensus filter. Secondly, a novel optimization process to update the consensus weights is proposed based on the information consensus filter. Finally, some numerical simulations are given, and the experiment results show that the proposed method achieves better performance than the existing consensus filter strategies.