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TITLE: Linear dynamic filtering with noisy input and output
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AUTHORS: Ivan Markovsky and Bart De Moor
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ABSTRACT: We establish the equivalence between the optimal least-squares state estimator for a linear time-invariant dynamic system with noise corrupted input and output, and an appropriately modified Kalman filter. The approach used is algebraic and the result shows that the noisy input/output filtering problem is not fundamentally different from the classical Kalman filtering problem. The result is illustrated with a simulation example.
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KEYWORDS: dynamic errors-in-variables model, Kalman filtering, optimal smoothing, total least squares.
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STATUS: In the proc. of 13th IFAC Symposium on System Identification (SYSID-2003), Rotterdam, The Netherlands, pages 1749-1754
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DATE OF ENTRY: 20 November 2002
@InProceedings{MD02a,
author = {I. Markovsky and B. {De Moor}},
title = {Linear dynamic filtering with noisy input and output},
booktitle = {13th IFAC Symposium on System Identification (SYSID-2003)},
pages = {1749--1754},
month = {Aug.},
year = {2003}
}