Create New Account
Login
Search or Buy Articles
Browse Journals
Browse Proceedings
Submit your Paper
Submission Information
Journal Review
Recommend to Your Library
Call for Papers
OPTIMAL FUSION REDUCED-ORDER KALMAN ESTIMATORS FOR DISCRETE-TIME STOCHASTIC SINGULAR SYSTEMS
S.L. Sun, Y.L. Shen, and J. Ma
References
[1] L. Dai, State estimation scheme in singular systems, Preprints of the 10th IFAC World Congress. Munich, Germany, 9, 1987, 211–215.
[2] M. Darouach, M. Zasadzinski, & M. Mehdi, State estimation for stochastic singular linear systems, International Journal of Systems Science, 24 (3), 1993, 345–354.
doi:10.1080/00207729308949493
[3] R. Nikoukhah, A.S. Willsky, & B.C. Levy, Kalman filtering and Riccati equation for descriptor systems. IEEE Transaction on Automatic Control, 37 (9), 1992, 1325–1340.
doi:10.1109/9.159570
[4] Y. Bar-Shalom, On the track-to-track correlation problem, IEEE Transaction on Automatic Control, 26 (2), 1981, 571–572.
doi:10.1109/TAC.1981.1102635
[5] H.R. Hashemipour, S. Roy, & A.J. Laub, Decentralized structures for parallel Kalman filtering, IEEE Transaction on Automatic Control, 33 (1), 1988, 88–93.
doi:10.1109/9.364
[6] N.A. Carlson, Federated square root filter for decentralized parallel processes, IEEE Transaction on Aerospace and Electronic Systems, 26 (3), 1990, 517–525.
doi:10.1109/7.106130
[7] S. Roy & H.R. Hashmipour, Decentralized linear estimation in correlated measurement noise, IEEE Transaction on Aerospace and Electronic Systems, 27 (6), 1991, 939–941.
doi:10.1109/7.104265
[8] R.K. Saha, An efficient algorithm for multisensor track fusion, IEEE Transaction on Aerospace and Electronic Systems, 34 (1), 1998, 200–210.
doi:10.1109/7.640278
[9] K.H. Kim, Development of track to track fusion algorithm. Proceeding of the American Control Conference, Maryland, 1994, 1037–1041.
[10] H. Chen, T. Kirubarajan, & Y. Bar-Shalom. Performance limits of track-to-track fusion vs. centralized estimation: theory and application, IEEE Transaction on Aerospace and Electronic Systems, 39 (2), 2003, 386–398.
doi:10.1109/TAES.2003.1207252
[11] X.R. Li, Y.M. Zhu, J. Wang, & C.Z. Han, Optimal linear estimation fusion – part I: unified fusion rules, IEEE Transactions on Information Theory, 49 (9), 2003, 2192–2208.
doi:10.1109/TIT.2003.815774
[12] S.L. Sun, Multi-sensor optimal information fusion Kalman filter with application, Aerospace Science and Technology, 8 (1), 2004, 57–62.
doi:10.1016/j.ast.2003.08.003
[13] S.L. Sun & Z.L. Deng, Multi-sensor optimal information fusion Kalman filter, Automatica, 40(6), 2004, 1017–1023.
doi:10.1016/j.automatica.2004.01.014
[14] S.L. Sun, Distributed optimal component fusion weighted by scalars for fixed-Lag Kalman smoother, Automatica, 41 (12), 2005, 2153–2159.
doi:10.1016/j.automatica.2005.06.014
[15] S.L. Sun & C.P. Zhang, Optimal information fusion distributed smoother for discrete multichannel ARMA signals, IEE Proceedings-Vision, Image, and Signal Processing, 152 (5), 2005, 583–589.
[16] S.L. Sun & Z.L. Deng, Distributed optimal fusion steady-state Kalman filter for systems with colored measurement noises. International Journal of Systems Science, 36 (3), 2005, 113–118.
doi:10.1080/00207720412331323280
[17] V.L. Syrmos & F.L. Lewis, Robust eigenvalue assignment for generalized systems, Automatica, 28 (6), 1992, 1223–1228.
doi:10.1016/0005-1098(92)90064-M
[18] B.D.O. Anderson & J.B. Moore, Optimal filtering, Englewood Cliffs, NJ )Prentice-Hall, 1979).
Important Links:
Abstract
DOI:
10.2316/Journal.201.2008.1.201-1614
From Journal
(201) Mechatronic Systems and Control (formerly Control and Intelligent Systems) - 2008
Go Back