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Nouvelles méthodes en filtrage particulaire-Application au recalage de navigation inertielle par mesures altimétriques

Abstract : In this report, the aim is to develop and study a new particle filter called «The Kalman-Particle Kernel Filter (KPKF)». The KPKF represents the conditional density of the state as a mixture of n-dimensional gaussian densities each centered on a particle and having a small covariance matrix. The algorithm corrects the system state both by a Kalman-type correction and a particle-type correction, by changing the particle weights. In addition an original resampling method is performed to keep the appropriate properties of gaussian mixture. The KPKF combines advantages of the Regularized Particle Filter (RPF) in term of robustness and of the Extended Kalman Filter (EKF) in term of accuracy. This new method of filtering is applied to inertial navigation update of an aircraft equipped with a radar altimeter. The results show a good behaviour of the KPKF for a large initial uncertainty of the aircraft?s position.
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https://tel.archives-ouvertes.fr/tel-00008068
Contributor : Karim Dahia <>
Submitted on : Friday, January 14, 2005 - 3:31:51 PM
Last modification on : Friday, November 6, 2020 - 3:49:56 AM
Long-term archiving on: : Friday, September 14, 2012 - 10:15:19 AM

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Karim Dahia. Nouvelles méthodes en filtrage particulaire-Application au recalage de navigation inertielle par mesures altimétriques. Mathématiques [math]. Université Joseph-Fourier - Grenoble I, 2005. Français. ⟨tel-00008068⟩

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