Non-Linear Filtering Approaches for INS/GPS Integration

Abstract : Navigation with an integrated INS/GPS approach requires to solve a set of nonlinear equations. In this case, nonlinear filtering techniques such as Particle Filtering methods are expected to perform better than the classical, but suboptimal, Extended Kalman Filter. Besides, the INS/GPS model has a conditionally linear Gaussian structure. A Rao-Blackwellization procedure can then be applied to reduce the variance of the state estimates. This paper studies different algorithms combining Rao-Blackwellization and particle filtering for a specific INS/GPS scenario. Simulation results illustrate the performance of these algorithms. The variance of the estimates is also compared to the corresponding posterior Cramer-Rao bound.
Type de document :
Communication dans un congrès
EUSIPCO 2004, 12th European Signal Processing Conference, Sep 2004, Vienna, Austria. pp 873-876, 2004
Liste complète des métadonnées

Littérature citée [7 références]  Voir  Masquer  Télécharger

https://hal-enac.archives-ouvertes.fr/hal-01021735
Contributeur : Laurence Porte <>
Soumis le : jeudi 30 octobre 2014 - 13:55:50
Dernière modification le : mercredi 23 mai 2018 - 17:58:09
Document(s) archivé(s) le : mardi 11 avril 2017 - 12:00:08

Fichier

126.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01021735, version 1

Citation

Audrey Giremus, Arnaud Doucet, Anne-Christine Escher, Jean-Yves Tourneret. Non-Linear Filtering Approaches for INS/GPS Integration. EUSIPCO 2004, 12th European Signal Processing Conference, Sep 2004, Vienna, Austria. pp 873-876, 2004. 〈hal-01021735〉

Partager

Métriques

Consultations de la notice

190

Téléchargements de fichiers

72