Abstract
The functions, which describe the time evolution of a dynamic system, are approximated by means of splines. The unknown spline coefficients are estimated by processing noisy measurements of observable system variables, by collocating the system differential equation, and by using a-priori information. The arising overdetermined linear algebraic system in the spline coefficients is solved in a weighted least squares sense, with weights equal to the inverses of the appropriate standard deviations.
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References
de Boor, C.: A practical guide to spline analysis, 1978.
Traas, C.R.: Digital filtering methods, with applications to spacecraft attitude determination in the presence of modelling errors NLR TR 79039 L, 1979.
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© 1982 Birkhäuser Verlag Basel
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Traas, C.R. (1982). Spline Approximation as a Tool for Estimation. In: Collatz, L., Meinardus, G., Werner, H. (eds) Numerical Methods of Approximation Theory, Vol.6 / Numerische Methoden der Approximationstheorie, Band 6. International Series of Numerical Mathematics / Internationale Schriftenreihe zur Numerischen Mathematik / Série internationale d’Analyse numérique, vol 59. Birkhäuser Basel. https://doi.org/10.1007/978-3-0348-7186-0_17
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DOI: https://doi.org/10.1007/978-3-0348-7186-0_17
Publisher Name: Birkhäuser Basel
Print ISBN: 978-3-0348-7188-4
Online ISBN: 978-3-0348-7186-0
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