Open AccessModified spectral method for optimal estimation in linear continuous-time stochastic systems
Author(s) -
К. А. Рыбаков
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1864/1/012025
Subject(s) - smoothing , discretization , representation (politics) , mathematical optimization , mathematics , spectral density estimation , maximum entropy spectral estimation , particle filter , spectral method , filter (signal processing) , series (stratigraphy) , optimal estimation , algorithm , computer science , stochastic process , statistics , mathematical analysis , paleontology , political science , law , principle of maximum entropy , computer vision , biology , fourier transform , politics
The spectral method to solve estimation problems for linear continuous-time stochastic systems with polynomial measurements is presented. It is based on both the spectral form of mathematical description (the representation of deterministic functions and random processes by orthogonal series) and the particle filter. The main goal of this work is to implement the continuous-time particle filter without a time discretization. The proposed spectral method provides the possibility to solve estimation problems such as filtering, smoothing and prediction.