Dynamic Systems Models by Josif A. Boguslavskiy (deceased)Mark Borodovsky

Author:Josif A. Boguslavskiy (deceased)Mark Borodovsky
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

5.8.4 Recurrent form of the SFF (RSFF) Algorithm

The process of the recurrent refinement of the vector of the estimation vector is composed of m(d, N) steps. At each step, in compliance with the principle of the decomposition of observations (outlined in Chap. 1), by the new (being updated) a priori (for this step!) data, a refinement occurs to the current estimation vector of vector and of a vector, composed of components of vector W(d, N), not yet used by the algorithm. The estimate of these components is their statistical forecast implemented after the algorithm has used a part of the components of the vector W(d, N). Simultaneously, one computes an estimation error covariance maxtrix reached at this step. At the last, m(d, N)th step, one has no forecast, and the last refinement to the vector and the definition of a total estimation error covariance matrix occur.

For step k of the computational process, we assume the following notations:The vector is composed of 3n components of the vector and of components

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