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Comparison of geometries for ionospheric tomography
Author(s) -
Sutton Eric,
Na Helen
Publication year - 1995
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1029/94rs02314
Subject(s) - a priori and a posteriori , tomography , orthonormal basis , basis (linear algebra) , basis function , iterative reconstruction , algorithm , resolution (logic) , orthogonal basis , set (abstract data type) , radial basis function , computer science , mathematics , image resolution , tomographic reconstruction , computer vision , geometry , artificial intelligence , mathematical analysis , optics , physics , philosophy , epistemology , quantum mechanics , artificial neural network , programming language
The distribution of electron density in the ionosphere can be imaged using computerized tomography techniques. Because of the limited view angle, resolution in the vertical direction is poor but can be improved by using a priori information in the reconstruction algorithm. The orthogonal decomposition algorithm provides a theoretical framework that unifies several traditional tomographic reconstruction algorithms, depending upon the choice of basis functions for the image domain. In this algorithm, the image is reconstructed as the weighted sum of a set of orthonormal basis functions. For ionospheric tomography, a priori information on the radial distribution of electron density can be used to guide the selection of basis functions. The resolution performance of the orthogonal decomposition algorithm depends upon the geometry used for the reconstruction. This paper analyzes three possible geometries. The factors that influence the selection of a particular geometry are (1) the ability to incorporate a priori information into the algorithm and (2) the ability to solve for the radial distribution. An analysis of the radial resolution in ionospheric tomography is also presented.