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Grzesiak Stefan (Uniwersytet Szczeciński)
O wyznaczaniu wartości początkowych algorytmu filtru Kalmana
On Determining the Initial Values of the Kalman Filter Algorithm
Przegląd Statystyczny, 1997, vol. 44, z. 1, s. 89-94, bibliogr. 13 poz.
Statistical Review
Filtry Kalmana, Modele stochastyczne
Kalman filters, Stochastic models
The article discusses several manners of determining initial values for the Kaiman filter algorithm. For this purpose, use can be made of: - the classical method of smallest squares, which, however, leads to ineffective estimators due to the nonfulfilment of the premises of this method; - the generalized method of smallest squares, for which it is possible to determine unbiased estimators, but only for a part of the set of possessed observations; - the application of an information filler, which is a much more complicated procedure and creates difficulties especially when not all parameters change in time; - the expanded Sarris approach, for which the basic problem is the necessity of reversing the co-variance matrix for a very large observation set. The best solution in a search for initial values, despite the above mentioned difficulties, appears to bei the approach proposed by Sarris.
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