Advanced signal processing techniques for GPR by taking into account the interface roughness of a stratified medium

Abstract : In this thesis, we focus on the development of new GPR methods to estimate the pavement structure. This thesis has two main objectives. First, it aims to improve the understanding of the scattering mechanisms for large-band radars in a stratified medium composed of rough interfaces. With increasing frequencies, pavement interfaces can no longer be considered as flat. The interface roughness must be taken into account in the propagation modelling. Thus, the influence of the roughness has been analysed. It has been shown that the interface roughness provides a continuous frequency decay of the magnitude of the echoes. This continuous frequency decay has then been introduced into the signal model. Secondly, several signal processing methods have been proposed to jointly estimate the roughness and thickness of pavement. Thus, multidimensional methods have been proposed by taking into account the roughness. Then, in order to reduce the computational burden, one-dimensional methods have also been proposed. From simulations, it can be seen that the proposed algorithms provide a good performance in parameter estimations (time delay, permittivity, roughness and thickness). Finally, the proposed signal processing methods are tested on experimental data. The results confirm the theoretical prediction. They show the feasibility to estimate both the thickness of thin pavements and roughness parameter.
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Meng Sun. Advanced signal processing techniques for GPR by taking into account the interface roughness of a stratified medium. Engineering Sciences [physics]. UNIVERSITE DE NANTES, 2016. English. ⟨tel-01379297⟩

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