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Filtration of a random process in a statistically uncertain linear stochastic differential system

  • Stochastic Systems
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Abstract

Minimax filtration of a process in a stochastic linear differential system with uncertain perturbation intensities for dynamics and observation models is studied. The filter is optimized by an integral quality criterion. Minimax filtering equations are derived from the solution of the dual optimization problem. A numerical filter designing method is described and its convergence is proved. Results of numerical experiments are given.

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Authors and Affiliations

  1. Moscow Aviation Institute (State Technical University), Moscow, Russia

    G. B. Miller & A. R. Pankov

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  1. G. B. Miller
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  2. A. R. Pankov
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Translated from Avtomatika i Telemekhanika, No. 1, 2005, pp. 59–71.

Original Russian Text Copyright © 2005 by Miller, Pankov.

This work was supported by the Russian Foundation for Basic Research, project no. 02-01-00361.

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Miller, G.B., Pankov, A.R. Filtration of a random process in a statistically uncertain linear stochastic differential system. Autom Remote Control 66, 53–64 (2005). https://doi.org/10.1007/s10513-005-0006-4

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  • DOI: https://doi.org/10.1007/s10513-005-0006-4

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