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Theses

Détection et Estimation en Environnement non Gaussien

Abstract : This thesis deals with radar detection in impulsive noise contexts. Indeed, under Gaussian assumptions, classical detectors, like Optimum Gaussian Detector, present several failures when the background scatterers are heterogeneous and non Gaussian, which is the case for ground or sea clutter. Clutter physical models based on compound noise modeling (SIRP, Compound Gaussian Processes) allow to correctly describe the reality (range power variations or clutter transitions areas). However, these models depend on several unknown parameters (covariance matrix, statistical distribution of the texture, disturbance parameters) which have to be estimated. When this estimation scheme is carried out, it is possible to build optimum radar detectors (Generalized Likelihood Ratio Test - Linear Quadratic) associated to this non Gaussian background. Based on these noise models, this thesis presents a complete analysis of several estimation schemes of the noise covariance matrix, associated to the detection problem. A statistical study of the main covariance matrix estimates which are used in the literature, is performed. Moreover, an improved estimate is proposed: the Fixed Point estimate, very attractive thanks to its good statistical and detection properties.
This thesis also describes detection performance and theoretical properties (texture-CFAR and matrix-CFAR) of the GLRT-LQ detector built with the studied covariance matrix estimates. In particular, the detector invariance to the texture distribution and to the covariance matrix structure is shown. Finally, these detectors are analyzed with simulated data and then, experimented on real ground clutter data.
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Contributor : Frédéric Pascal <>
Submitted on : Thursday, February 1, 2007 - 11:40:06 AM
Last modification on : Friday, June 26, 2020 - 2:04:02 PM
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  • HAL Id : tel-00128438, version 1

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Frédéric Pascal. Détection et Estimation en Environnement non Gaussien. Traitement du signal et de l'image [eess.SP]. Université de Nanterre - Paris X, 2006. Français. ⟨tel-00128438⟩

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