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This article is cited in 5 scientific papers (total in 5 papers)
Normal suboptimal filtering for differential stochastic systems with unsolved derivatives
I. N. Sinitsyn Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Abstract:
The article develops the series of papers dedicated to stochastic systems with unsolved derivatives. Methodological aspects of normal suboptimal filterings (NSOF) for stochastic systems with unsolved derivatives are presented. Nonlinear differential equations for state and observation are given at the following conditions: observation equations are Gaussian and do not depend on the state variable. One of sections is devoted to NSOF for Gaussian and non-Gaussian systems. Corresponding NSOF are given for additive noises. Also, an illustrative example is given. The NSOF quality analysis is considered.
Keywords:
method of analytical modeling (MAM), method of normal approximation (MNA), method of statistical linearization (MSL), normal suboptimal filter, stochastic system (StS), stochastic systems with unsolved derivatives, shaping filter.
Received: 29.06.2020
Citation:
I. N. Sinitsyn, “Normal suboptimal filtering for differential stochastic systems with unsolved derivatives”, Inform. Primen., 15:1 (2021), 3–10
Linking options:
https://www.mathnet.ru/eng/ia705 https://www.mathnet.ru/eng/ia/v15/i1/p3
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