Accurately estimating the state of a dynamical system is of fundamental importance in a variety of applications, from engineering challenges to everyday life. This task is complex because uncertainties typically affect the dynamical behaviour as well as the available observations of the (hidden) state. The goal of this chapter is to provide a comprehensive overview, from the probabilistic problem statement to methods for its solution. In particular the focus will be on filtering problems for time-continuous state evolution equations and time-discrete observations. It will be shown that, except for very few cases, the filtering problem has no closed-form solution, which is generally infinite-dimensional. Hence, several practical algorithms to find an approximate solution are presented.
Fundamentals of Filtering
Optimization Under Uncertainty with Applications to Aerospace Engineering ; Chapter : 6 ; 181-222
2020-09-10
42 pages
Article/Chapter (Book)
Electronic Resource
English
State estimation , Uncertainty propagation , Inference , Navigation , Filtering algorithms Physics , Astronomy, Astrophysics and Cosmology , Aerospace Technology and Astronautics , Optimization , Mathematical and Computational Engineering , Computational Science and Engineering , Physics and Astronomy
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