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Filtrage particulaire et ouverture synthétique inverse sur cibles RADAR non-coopératives

Abstract : This report describes the application of optimal nonlinear/non-Gaussian filtering to the radar signal processing problem. This approach, made feasible by a new technique named Particle Filtering, may cope with nonlinear models without any restrictions as well as non-Gaussian dynamic and observation noises. The main feature of the Particle Filtering is that it constructs the conditional probability of the state variables, with respect to the measurements, through a random exploration of the state space by entities called particles. A weight is assigned to each particle by a Bayes correction term based on the measurements. The application of this new filter to the inverse synthetic aperture radar (ISAR) technique allows the joint estimation of the path and the image of a manoeuvring target in weak signal to noise ratio situations. The same algorithm can be used also to deal with the simpler problem of target tracking in presence of glint.
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Contributor : Emilie Marchand <>
Submitted on : Tuesday, April 3, 2007 - 1:54:52 PM
Last modification on : Friday, January 10, 2020 - 9:08:08 PM
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  • HAL Id : tel-00139730, version 1


Marco Antonio Chamon. Filtrage particulaire et ouverture synthétique inverse sur cibles RADAR non-coopératives. Automatique / Robotique. Ecole nationale superieure de l'aeronautique et de l'espace, 1996. Français. ⟨tel-00139730⟩



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