Journal of Applied Mathematics

  • J. Appl. Math.
  • Volume 2013, Special Issue (2013), Article ID 683249, 9 pages.

Distributed Filter with Consensus Strategies for Sensor Networks

Xie Li, Huang Caimou, and Hu Haoji

Full-text: Open access

Abstract

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.

Article information

Source
J. Appl. Math., Volume 2013, Special Issue (2013), Article ID 683249, 9 pages.

Dates
First available in Project Euclid: 14 March 2014

Permanent link to this document
https://projecteuclid.org/euclid.jam/1394806119

Digital Object Identifier
doi:10.1155/2013/683249

Mathematical Reviews number (MathSciNet)
MR3122118

Zentralblatt MATH identifier
06950818

Citation

Li, Xie; Caimou, Huang; Haoji, Hu. Distributed Filter with Consensus Strategies for Sensor Networks. J. Appl. Math. 2013, Special Issue (2013), Article ID 683249, 9 pages. doi:10.1155/2013/683249. https://projecteuclid.org/euclid.jam/1394806119


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