نبذة مختصرة : The objective of radar imaging is to characterize the observed target. In the case of forest remote sensing, the objective is to extract the component of the vegetation physical parameters.This manuscript addresses the problem of the inversion of electromagnetic data for low frequency wave, VHF band to the P band. In these frequency bands, the canopy (leaves and small branches) does not almost interact with the radar wave and the forest can thus, in first approximation, be represented by vertical cylinders (trunks) and tilted (primary branches).In this context, the numerical electromagnetic methods of inversion lean on models which calculate, many times, the scattered fields radiated by such broadcasters. It is then necessary to choose a physical model which compromise speed/accuracy tilts in favor of the speed, thus a "approached" model. The exactness of the chosen model is then studied and then validated by comparison to a model which the compromise speed/accuracy is inverted, thus a "exact" model. Among the many numerical methods of inversion, that of the genetic algorithm (AG) was chosen. This algorithm, well known, is analyzed here then improved to meet the requirements of the composed electromagnetic problem. It is then validated on simulated and measured data. This validation is also an opportunity to study the impact of the set of data used on the speed and the precision of the inversion, according to the configurations of antenna (frequencies, positions, polarizations). ; La problématique de l'imagerie radar pose comme objectif de caractériser la cible observée. Dans le contexte de la télédétection appliquée aux milieux forestiers, il s'agit d'extraire les paramètres physiques constitutifs de la végétation.Ce manuscrit traite donc de la problématique de l'inversion de données électromagnétiques pour les basses fréquences radar, de la bande VHF à la bande P. Dans ces bandes de fréquences la canopée (feuilles et petites branches) n'interagit quasiment pas avec l'onde radar et la forêt peut donc, en ...
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