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Titre du document / Document title

Particle flow for nonlinear filters with log-homotopy

Auteur(s) / Author(s)

DAUM Fred ; HUANG Jim ;

Résumé / Abstract

We describe a new nonlinear filter that is vastly superior to the classic particle filter. In particular, the computational complexity of the new filter is many orders of magnitude less than the classic particle filter with optimal estimation accuracy for problems with dimension greater than 2 or 3. We consider nonlinear estimation problems with dimensions varying from 1 to 20 that are smooth and fully coupled (i.e. dense not sparse). The new filter implements Bayes' rule using particle flow rather than with a pointwise multiplication of two functions; this avoids one of the fundamental and well known problems in particle filters, namely particle collapse as a result of Bayes' rule. We use a log-homotopy to derive the ODE that describes particle flow. This paper was written for normal engineers, who do not have homotopy for breakfast.

Revue / Journal Title

Proceedings of SPIE, the International Society for Optical Engineering    ISSN  0277-786X   CODEN PSISDG 

Source / Source

Congrès
Signal and data processing of small targets 2008 :   ( 18-20 March 2008, Orlando, Florida, USA )
Signal and data processing of small targets, Orlando FL , ETATS-UNIS (2008)
2008  , vol. 6969, pp. 696918.1-696918.12[Note(s) : 1 v. (various pagings), ] (19 ref.) ISBN 978-0-8194-7160-4 ; 0-8194-7160-7 ;  Illustration : Illustration ;

Langue / Language

Anglais

Editeur / Publisher

Society of Photo-Optical Instrumentation Engineers, Bellingham, WA, ETATS-UNIS  (1981) (Revue)
SPIE, Bellingham, Wash., ETATS-UNIS  (2008) (Monographie)

Mots-clés anglais / English Keywords

Bayes methods

;

Implementation

;

Nonlinear problems

;

Accuracy

;

Optimal estimation

;

Computational complexity

;

Particle filter

;

Homotopy

;

Non linear filter

;

Mots-clés français / French Keywords

0130C

;

Méthode Bayes

;

Implémentation

;

Problème non linéaire

;

Précision

;

Estimation optimale

;

Complexité calcul

;

Filtre particule

;

Homotopie

;

Filtre non linéaire

;

Mots-clés espagnols / Spanish Keywords

Implementación

;

Precisión

;

Estimación óptima

;

Complejidad computación

;

Filtro partículas

;

Homotopía

;

Filtro no lineal

;

Localisation / Location

INIST-CNRS, Cote INIST : 21760, 35400017286973.0390

Nº notice refdoc (ud4) : 20917104



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