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Title: Kalman filter sensitivity with respect to parametric noises uncertainty (English)
Author: Madjarov, Nikola
Author: Mihaylova, Ludmila
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 32
Issue: 3
Year: 1996
Pages: 307-322
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Category: math
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MSC: 93C70
MSC: 93E11
idZBL: Zbl 0874.93087
idMR: MR1438222
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Date available: 2009-09-24T19:02:54Z
Last updated: 2012-06-06
Stable URL: http://hdl.handle.net/10338.dmlcz/125513
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Reference: [1] V. Angelova N. Christov, P. Petkov: Perturbation and numerical analysis of Kalman filters.Automatics \& Informatics (1993), 5/6, 19-20 (in Bulgarian).
Reference: [2] K. Birmiwal, J. Shen: Optimal robust filtering.Statist. Decisions 11 (1993), 101-119. Zbl 0790.62089, MR 1238479
Reference: [3] B. Carew, P. Bélanger: Identification of optimum filter steady-state gain for systems with unknown noise covariances.IEEE Trans. Automat. Control 18 (1973), 6, 582-587. MR 0441498
Reference: [4] P. Gahinet, A. Laub: Computable bounds for the sensitivity of algebraic Riccati equation.SIAM J. Control Optim. 28 (1990), 6, 1461-1480. MR 1075213
Reference: [5] R. E. Griffin, A. P. Sage: Large and small scale sensitivity analysis of optimum estimation algorithms.IEEE Trans. Automat. Control 13 (1968), 4, 320-329. MR 0249176
Reference: [6] R. E. Griffin, A. P. Sage: Sensitivity analysis of discrete filtering and smoothing algorithms.AIAA J. 7 (1969), 10, 1890-1897. Zbl 0193.15701
Reference: [7] N. S. Gritsenko, al: Adaptive estimation: a survey.Zarubezhnaya Radioelectronica (1983), 7, 3-27 and (1985), 3, 3-26 (in Russian).
Reference: [8] A. H. Jazwinski: Stochastic Processes and Filtering Theory.Academic Press, New York 1970. Zbl 0203.50101
Reference: [9] R. E. Kalman: A new approach to linear filtering and prediction problems.Trans. ASME, J. Basic Engrg. 82D (1960), 34-45.
Reference: [10] C. Kenney, G. Hewer: The sensitivity of the algebraic and differential Riccati equations.SIAM J. Control Optim. 28 (1990), 1, 50-69. Zbl 0695.65025, MR 1035972
Reference: [11] B. Kovačević Ž. Durović, S. Glavaški: On robust Kalman filtering.Internat. J. Control 56 (1992), 3, 547-562. MR 1181998
Reference: [12] D. G. Lainiotis, F. L. Sims: Sensitivity analysis of discrete Kalman filters.Internat. J. Control 12 (1970), 4, 657-669. Zbl 0199.49204
Reference: [13] N. Madjarov, L. Mihaylova: Sensitivity analysis of linear optimal stochastic observers.In: Proc. of the IEEE Internat. Conf. on Systems, Man and Cybernetics, Systems Engineering in the Service of Humans. Le Touquet, France 1993, pp. 482-487.
Reference: [14] N. Madjarov, L. Mihaylova: Sensitivity of Kalman filters.Automatics \& Informatics (1993), 1/2, 1-18 (in Bulgarian). Zbl 0825.93814
Reference: [15] N. Madjarov, L. Mihaylova: Kalman filters under stochastic uncertainty.In: Proc. of the Tenth Internat. Conf. on Systems Engineering, Coventry 1994, 756-763.
Reference: [16] C. J. Masreliez, R. D. Martin: Robust Bayesian estimation for the linear model and robustifying the Kalman filter.IEEE Trans. Automat. Control 22 (1977), 3, 361-371. Zbl 0354.93054, MR 0453124
Reference: [17] A. I. Matasov: The Kalman-Bucy filter accuracy in the guaranteed parameter estimation problem with uncertain statistics.IEEE Trans. Automat. Control 39 (1994), 3, 635-639. Zbl 0815.93081, MR 1268311
Reference: [18] V. Mathews, Z. Xie: A stochastic gradient adaptive filter with gradient adaptive step size.IEEE Trans. Sign. Process. 41 (1993), 6, 2075-2087. Zbl 0775.93269
Reference: [19] R. K. Mehra: Approaches to adaptive filtering.IEEE Trans. Automat. Control 11 (1972), 5, 693-698. Zbl 0261.93036, MR 0441510
Reference: [20] A. Moghaddamjoo: Approaches to adaptive Kalman filtering: a survey.Control Theory and Adv. Tech. 5 (1989), 1, 1-18. MR 0991227
Reference: [21] J. M. Morris: The Kalman filter: A robust estimator for some classes of linear quadratic problems.IEEE Trans. Inform. Theory 22 (1976), 5, 526-534. Zbl 0336.93037, MR 0419040
Reference: [22] T. Nishimura: Modeling errors in Kalman filters.In: Theory and Application of Kalman Filtering (C.T. Leondes, ed.), Chapter 4, 1970, AGARDograph No. 139.
Reference: [23] M. Ogarkov: Methods for Statistical Estimation of Random Processes Parameters.Energoatomizdat, Moscow 1990 (in Russian). MR 1192134
Reference: [24] R. V. Patel, M. Toda: Bounds on performance of non stationary continuous-time filters under modeling uncertainty.Automatica 20 (1984), 1, 117-120.
Reference: [25] S. Sangsuk-Iam, T. Bullok: Analysis of continuous-time Kalman filtering under incorrect noise covariances.Automatica 24 (1988), 5, 659-669. MR 0966690
Reference: [26] S. Sangsuk-Iam, T. Bullok: Analysis of discrete-time Kalman filtering under incorrect noise covariances.IEEE Trans. Automat. Control 35 (1990), 12, 1304-1308. MR 1078143
Reference: [27] L. L. Scharf, D. L. Alspach: On stochastic approximation and an adaptive Kalman filter.In: Proc. of the IEEE Decision and Control Conference, 1972, pp. 253-257.
Reference: [28] N. K. Sinha: Adaptive Kalman filtering using stochastic approximation.Electr. Letters 9 (1973), 819, 177-178.
Reference: [29] N. K. Sinha, A. Tom: Adaptive state estimation systems with unknown noise covariances.Internat. J. Systems Sci. 8 (1977), 4, 377-384.
Reference: [30] D. A. Stratton, R. F. Stengel: Robust Kalman filter design for predictive wind shear detection.IEEE Trans. Aerospace Electron. Systems 29 (1993), 4, 1185-1193.
Reference: [31] M. Toda, R. V. Patel: Bounds on estimation errors of discrete-time filters under modeling uncertainty.IEEE Trans. Automat. Control 26 (1980), 6, 1115-1121. Zbl 0485.93068, MR 0601493
Reference: [32] Ya. Z. Tsypkin: Foundations of Informational Identification Theory.Nauka, Moscow 1984 (in Russian). MR 0783831
Reference: [33] W. Vetter: Matrix calculus operations and Taylor expansions.SIAM Rev. 15 (1973), 2, 352-369. Zbl 0254.65033, MR 0340513
Reference: [34] L. Xie, Y. Soh: Robust Kalman filtering for uncertain systems.Systems Control Lett. 22 (1994), 123-129. Zbl 0792.93118, MR 1261851
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