IEEE Transactions on Geoscience and Remote Sensing · 2008 · 69 citations · 22 references
Natural SciencesEarth SciencesGeophysicsDiagnostic ImagingGeodesyHybrid ImagingGeophysical InversionImage ReconstructionElectron DensityIll-posed Inverse ProblemsIll-posed ProblemsIterative ImprovementSingular Value DecompositionTomographic InversionTomographic ReconstructionTomography
In this paper, a hybrid reconstruction algorithm (HRA) is presented to solve the ill-posed inverse problem associated with 3-D ionospheric stochastic tomography. In this new method, the ionospheric electron density (IED) can be inverted by using two steps. First, a truncated singular value decomposition (TSVD) method, whose value is independent on any initial estimation, is used to resolve the ill-posed problem of the tomography system. Second, taking into account the "approximation" of its solution, an iterative improvement process of the solution is then implemented by utilizing the conventional algebraic reconstruction algorithm (ART). The HRA, therefore, offers a more reasonable approach to choose an initial approximate for the ART and to improve the quality of the final reconstructed image. A simulated experiment demonstrates that the HRA method is superior to the TSVD or the ART alone for the tomographic inversion of IED. Finally, the HRA is used to perform GPS-based tomographic reconstruction of the IED at mid- and low-latitude regions.
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The truncatedSVD as a method for regularization
Per Christian Hansen · BIT Numerical Mathematics · 1987 · 815 citations