A Tutorial on Particle Filtering and Smoothing: Fifteen years later

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ID: 294508
2008
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Abstract
Optimal estimation problems for non-linear non-Gaussian state-space models do not typically admit analytic solutions. Since their introduction in 1993, particle filtering methods have become a very popular class of algorithms to solve these estimation problems numerically in an online manner, i.e. recursively as observations become available, and are now routinely used in fields as diverse as computer vision, econometrics, robotics and navigation. The objective of this tutorial is to provide a complete, up-to-date survey of this field as of 2008. Basic and advanced particle methods for filtering as well as smoothing are presented.
Reference Key
openalex_W2111787305 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Arnaud Doucet, Adam M. Johansen
Journal Oxford University Press eBooks
Year 2008
DOI
DOI not found
URL
http://automatica.dei.unipd.it/tl_files/utenti/lucaschenato/Classes/PSC10_11/Tutorial_PF_doucet_johansen.pdf
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