Journal Menu
- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 238597, 12 pages
doi:10.1155/2012/238597
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.
Linked References
- D. L. Hall and J. Llinas, “An introduction to multisensor data fusion,” Proceedings of the IEEE, vol. 85, no. 1, pp. 6–23, 1997. View at Scopus
- H. F. Durrant-Whyte, B. Y. S. Rao, and H. Hu, “Toward a fully decentralized architecture for multi-sensor data fusion,” in Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1331–1336, May 1990. View at Scopus
- R. Olfati-Saber, “Distributed Kalman filtering for sensor networks,” in Proceedings of the 46th IEEE Conference on Decision and Control (CDC '07), pp. 5492–5498, December 2007. View at Publisher · View at Google Scholar · View at Scopus
- B. Sinopoli, L. Schenato, M. Franceschetti, K. Poolla, M. I. Jordan, and S. S. Sastry, “Kalman filtering with intermittent observations,” IEEE Transactions on Automatic Control, vol. 49, no. 9, pp. 1453–1464, 2004. View at Publisher · View at Google Scholar
- L. Shi, “Kalman filtering over graphs: theory and applications,” IEEE Transactions on Automatic Control, vol. 54, no. 9, pp. 2230–2234, 2009. View at Publisher · View at Google Scholar
- P. Alriksson and A. Rantzer, “Experimental evaluation of a distributed Kalman filter algorithm,” in Proceedings of the 46th IEEE Conference on Decision and Control (CDC '07), pp. 5499–5504, December 2007. View at Publisher · View at Google Scholar · View at Scopus
- M. Epstein, L. Shi, and R. M. Murray, “An estimation algorithm for a class of networked control systems using UDP-like communication schemes,” in Proceedings of the 45th IEEE Conference on Decision and Control (CDC '06), pp. 5597–5603, December 2006. View at Scopus
- P. J. Huber, Robust Statistics, John Wiley & Sons, New York, NY, USA, 2nd edition, 1981, Wiley Series in Probability and Mathematical Statistics.
- J. Mattingely and S. Boyd, “Real-time convex optimization in signal processing,” IEEE Signal Processing Magazine, vol. 27, no. 3, pp. 50–61, 2010. View at Publisher · View at Google Scholar · View at Scopus
- A. Alessandri, M. Baglietto, and G. Battistelli, “A maximum-likelihood Kalman filter for switching discrete-time linear systems,” Automatica, vol. 46, no. 11, pp. 1870–1876, 2010. View at Publisher · View at Google Scholar · View at Scopus
- D. Y. Kim, J. H. Yoon, Y. H. Kim, and V. Shin, “Distributed information fusion filter with intermittent observations,” in Proceedings of the 13th Conference on Information Fusion (FUSION '10), July 2010. View at Scopus
- H. A. P. Blom and Y. Bar-Shalom, “Interacting multiple model algorithm for systems with Markovian switching coefficients,” IEEE Transactions on Automatic Control, vol. 33, no. 8, pp. 780–783, 1988. View at Publisher · View at Google Scholar · View at Scopus