A new autocovariance least-squares method for estimating noise covariances

Automatica

Volumn 42, Issue 2, 2006, Pages 303-308

  Odelson, Brian J ^a   Rajamani, Murali R ^b   Rawlings, James B ^a,b,c  

^a BP Research and Technology ^*  (United States)

^b University of Wisconsin Madison   (United States)

^c UNIVERSITY OF WISCONSIN   (United States)

Author keywords

Adaptive Kalman filter; Covariance estimation; Optimal estimation; Semidefinite programming; State estimation

Indexed keywords

ADAPTIVE KALMAN FILTER; COVARIANCE ESTIMATION; OPTIMAL ESTIMATION; SEMIDEFINITE PROGRAMMING;

ADAPTIVE FILTERING; KALMAN FILTERING; PREDICTIVE CONTROL SYSTEMS; PROBLEM SOLVING; STATE ESTIMATION;

CONTROL SYSTEM ANALYSIS;

EID: 29244454276     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2005.09.006     Document Type: Article

References (20)

1. D.L. Alspach A parallel filtering algorithm for linear systems with unknown time-varying noise statistics IEEE Transactions on Automatic Control 19 5 1974 552 556
2. A. Averbuch, S. Itzikowitz, and T. Kapon Radar target tracking - viterbi versus IMM IEEE Transactions on Aerospace and Electronic Systems 27 3 1991 550 563
3. M.S. Bartlett On the theoretical specification of sampling properties of autocorrelated time series Journal of the Royal Statistical Society Supplement 8 1946 27 41
4. P.R. Bélanger Estimation of noise covariance matrices for a linear time-varying stochastic process Automatica 10 1974 267 275
5. Bohlin, T. (1976). Four cases of identification of changing systems. In R. K. Mehra, & D. G. Lainiotis (Eds.), System identification: Advances and case studies (1st ed.). New York: Academic Press.
6. J. Brewer Kronecker products and matrix calculus in system theory IEEE Transactions on Circuits and Systems 25 9 1978 772 781
7. B. Carew, and P.R. Bélanger Identification of optimum filter steady-state gain for systems with unknown noise covariances IEEE Transactions on Automatic Control 18 6 1973 582 587
8. C.G. Hilborn, and D.G. Lainiotis Optimal estimation in the presence of unknown parameters IEEE Transactions on Systems, Science, and Cybernetics 5 1 1969 38 43
9. Jenkins, G. M., & Watts, D. G. (1968). Spectral analysis and its applications. 500 Sansome Street, San Fransisco, CA: Holden-Day.
10. R.L. Kashyap Maximum likelihood identification of stochastic linear systems IEEE Transactions on Automatic Control 15 1 1970 25 34
11. C.L. Lawson, and R.J. Hanson Solving least squares problems 1995 SIAM Philadelphia, PA
12. R.K. Mehra On the identification of variances and adaptive Kalman filtering IEEE Transactions on Automatic Control 15 12 1970 175 184
13. R.K. Mehra Approaches to adaptive filtering IEEE Transactions on Automatic Control 17 1972 903 908
14. K.A. Myers, and B.D. Tapley Adaptive sequential estimation with unknown noise statistics IEEE Transactions on Automatic Control 21 1976 520 523
15. C. Neethling, and P. Young Comments on "Identification of optimum filter steady-state gain for systems with unknown noise covariances" IEEE Transactions on Automatic Control 19 5 1974 623 625
16. J. Nocedal, and S.J. Wright Numerical optimization 1999 Springer New York
17. G. Noriega, and S. Pasupathy Adaptive estimation of noise covariance matrices in real-time preprocessing of geophysical data IEEE Transactions on Geoscience Remote Sensing 35 5 1997 1146 1159
18. S.R. Searle Matrix algebra useful for statistics 1982 Wiley New York
19. L. Vandenberghe, and S. Boyd Semidefinite programming SIAM Review 38 1 1996 49 95
20. Wolkowicz, H., Saigal, R., & Vandenberghe, L. (Eds.). (2000). Handbook of semidefinite programming: Theory, algorithms and applications. MA: Kluwer Academic Publishers.