New Phase Noise Estimation And Correction For Interferometric Synthetic Aperture Radar Phase Unwrapping
This thesis proposes a solution method and builds a new algorithm solver that integrates both phase noise issue and mathematical ill posed measurement problem, in order to address the refractory problem of two dimensional phase unwrapping, by adopting an ordered statistical filter, guided by coheren...
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Format: | Thesis |
Published: |
2019
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Summary: | This thesis proposes a solution method and builds a new algorithm solver that integrates both phase noise issue and mathematical ill posed measurement problem, in order to address the refractory problem of two dimensional phase unwrapping, by adopting an ordered statistical filter, guided by coherency map, dedicated for interferometric synthetic aperture radar applications. The proposed algorithm solver attacks the phase discontinuity problem in different ways that integrates both phase unwrapping issue and denoising issue into single problem of phase ambiguity problem. In this thesis, important insights are gained based on the behaviour studies of existing mandatory InSAR phase unwrapping method and the statistical analytic works of InSAR phase noise. Such insights enable the accomplishment of a non-linear solution method that capable to preserve information and filter off the unwanted noise. The algorithm solver is tested under several pure InSAR simulated scenes and validated through the non-linear scenarios based on both simulated data and real data. For benchmarking, the thesis also presents up-to-date evaluations to assess the performance of our developed algorithm solver as compared to existing mandatory InSAR algorithm. For practical application, the InSAR real satellite data samples that integrated over developed algorithm with InSAR multi-baseline approach based on four dimensional imaging is presented. A new working scheme that able to overcome the InSAR limitation of multiple scatterers and extracts the deformation map and velocity map is suggested. |
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