- About this Journal ·
- Aims and Scope ·
- Article Processing Charges ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Recently Accepted Articles ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
ISRN Signal Processing
Volume 2012 (2012), Article ID 625897, 5 pages
On the Convergence of the Modified Riccati Equation
1Department of Electronics, Technological Educational Institute of Lamia, 35100 Lamia, Greece
2Department of Computer Science and Biomedical Informatics, University of Central Greece, 35100 Lamia, Greece
Received 5 March 2012; Accepted 26 April 2012
Academic Editors: C.-W. Kok and C.-M. Kuo
Copyright © 2012 Nicholas Assimakis and Maria Adam. 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.
- T. E. Fortmann, Y. Bar-Shalom, M. Scheffe, and S. Gelfand, “Detection thresholds for tracking in clutter—a connection between estimation and signal processing,” IEEE Transactions on Automatic Control, vol. 30, no. 3, pp. 221–229, 1985.
- Y. Boers and H. Driessen, “Tracking performance prediction and evaluation: the modified Riccati equation,” in Signal and Data Processing of Small Targets (SPIE '05), August 2005.
- Y. Boers and H. Driessen, “Results on the modified Riccati equation: target tracking applications,” IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 1, pp. 379–384, 2006.
- A. S. Chhetri, D. Morrell, and A. Papandreou-Suppappola, “Nonmyopic sensor scheduling and its efficient implementation for target tracking applications,” Eurasip Journal on Applied Signal Processing, vol. 2006, Article ID 31520, 2006.
- A. Farina, A. Di Lallo, L. Timmoneri, T. Volpi, and B. Ristic, “CRLB and ML for parametric estimate: new results,” Signal Processing, vol. 86, no. 4, pp. 804–813, 2006.
- M. Hernandez, B. Ristic, A. Farina, and L. Timmoneri, “A comparison of two Cramér-Rao bounds for nonlinear filtering with ,” IEEE Transactions on Signal Processing, vol. 52, no. 9, pp. 2361–2370, 2004.
- C. O. Savage and B. F. La Scala, “Sensor management for tracking smart targets,” Digital Signal Processing, vol. 19, no. 6, pp. 968–977, 2009.
- B. Ristic, S. Arulampalam, and N. Gordon, Beyond the Kalman Filter—Particle Filters for Tracking Applications, Artech House, Boston, Mass, USA, 2002.
- 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.
- J. H. Zwaga and H. Driessen, “Tracking performance constrained MFR parameter control: applying constraints on prediction accuracy,” in Proceedings of the 8th International Conference on Information Fusion (FUSION '05), vol. 1, p. 6, July 2005.
- B. D. O. Anderson and J. B. Moore, Optimal Filtering, Dover Publications, New York, NY, USA, 2005.
- R. E. Kalman, “A new approach to linear filtering and prediction problems,” Journal of Basic Engineering, Transactions on the ASME, vol. 82, pp. 34–45, 1960.
- H. Nguyen, J. Zhang, and B. Raghothaman, “A Kalman-filter approach to equalization of CDMA downlink channels,” Eurasip Journal on Applied Signal Processing, vol. 2005, no. 5, Article ID 750826, 2005.
- N. Assimakis, A. Kechriniotis, S. Voliotis, F. Tassis, and M. Kousteri, “Analysis of the time invariant Kalman filter implementation via general Chandrasekhar algorithm,” International Journal of Signal and Imaging Systems Engineering, vol. 1, no. 1, pp. 51–57, 2008.