The Kalman Filter: A Robust Estimator for Some Classes of Linear Quadratic Problems

IEEE Transactions on Information Theory

Volumn 22, Issue 5, 1976, Pages 526-534

  Morris, Joel M ^a  

^a NAVAL RESEARCH LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 13544258953     PISSN: 00189448     EISSN: 15579654     Source Type: Journal    
DOI: 10.1109/TIT.1976.1055611     Document Type: Article

References (10)

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2. R. Bellman, Introduction to Matrix Analysis, 2nd, ed. New York, NY: McGraw-Hill, 1970.
3. A. E. Bryson, Jr. and Y. C. Ho, Applied Optimal Control. Waltham, MA: Ginn and Co., 1969.
4. Y. C. Ho, “On the minimax principle and zero-sum stochastic differential games,” Tech. Rep. No. 630, Div. Engineering and Applied Physics, Harvard University, Cambridge, MA, Apr. 1972.
5. R. E. Kaiman “A new approach to linear filtering and prediction problems,” Trans. ASME J. of Basic Engineering, vol. 82D, pp. 35–45, Mar. 1960.
6. L. Meyer, R. E. Larson, and A. J. Korsak, “Optimal filtering with quantized data,” Proceedings of the JACC, 1968.
7. M. Mintz, “A Kaiman filter as a minimax estimator,” J. Optimization Theory and Applications, vol. 9, 1972.
8. N. E. Nahi, Estimation Theory and Applications. New York, NY: Wiley, 1969.
9. T. Nishimura “Error bounds of continuous Kaiman filters and the application to orbit determination problems,” IEEE Trans. Automat. Contr., vol. AC-12, pp. 268–275, June 1967.
10. V. D. VandeLinde, “Optimal observation policies in linear stochastic systems,” Ph.D. dissertation, Carnegie-Mellon Univ., Pittsburgh, PA, 1967.