Méthodes d'inversion pour la reconstruction de mines enfouies à partir de mesures d'antennes radar.

Abstract : This work is part of the FUI Tandem project on radar imaging of mines buried in dry ground by heliborne antennas. The antenna data correspond to measurements of the electromagnetic field (component tangential to the antenna) in the back-scattering configuration: a single transmitter/transceiver antenna. The primary objective of the thesis is to validate / modify the SAR (Synthetic Aperture Radar) methodology proposed by engineers to process the antenna data and to image the mines. The main difficulty lies in the fact that the SAR method is based on the principle of a homogeneous background whereas the study case is not. We have studied the incorporation of a two-layer approximation of the reference medium to correct the effect of the soil and to obtain images that are less sensitive to the effect of the latter. The first solution consists in mimicking the SAR technique to construct an indicator of the geometry via the back propagation of the data in the bi-layer medium using the formula given by the Born approximation. The second option, much more costly numerically consists in inverting the Born model with a regularization technique of the total variation type. In a second part, we are interested in adapting MUSIC (MUltiple SIgnal Classification) methods to retrieve the "depth" information not provided by SAR methods. Based on the Tandem experiement, we proposed the extension of these methods to the case of data in quasi-back-scattering configuration: a transmitting antenna coupled to a 1D array of receiving antennas. The methodology is completely new and the justification of the method is based on the asymptotic analysis of the scattering problem in the small obstacle and far field regime. The study was also extended to cylindrical configurations that could be adapted to biomedical imaging.
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Mohamed Lakhal. Méthodes d'inversion pour la reconstruction de mines enfouies à partir de mesures d'antennes radar.. Equations aux dérivées partielles [math.AP]. Université Paris-Saclay, 2017. Français. ⟨NNT : 2017SACLX034⟩. ⟨tel-01724695⟩

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