Open AccessCouscous-constant approximation in signal filtration task
Author(s) -
Evgeniy Butyrskiy
Publication year - 2021
Publication title -
nacionalʹnaâ bezopasnostʹ i strategičeskoe planirovanie
Language(s) - English
Resource type - Journals
ISSN - 2307-1400
DOI - 10.37468/2307-1400-2021-1-34-43
Subject(s) - kalman filter , linear approximation , constant (computer programming) , filtration (mathematics) , nonlinear system , approximation error , task (project management) , signal (programming language) , filter (signal processing) , mathematics , signal processing , state (computer science) , matrix (chemical analysis) , sampling (signal processing) , computer science , algorithm , digital signal processing , statistics , physics , engineering , materials science , systems engineering , quantum mechanics , computer hardware , composite material , computer vision , programming language
The paper considers the task of assessing the state of a nonlinear dynamic system, based on the couscous-linear approximation of non-linear functions included in the state and observa-tion equation. Examples of the method presented in filtration tasks are given and it is shown that the use of couscous-linear approximation allows at least half the margin of sampling error by the Kalman-Busey filter compared to the first-order approximation. Dynamic systems and processing algorithms in the form of vector-matrix equations have been obtained for multidi-mensional systems.