Abstract
Tomographic processing of path integral electron density records is emerging as a viable tool for ionospheric research. Tomographic processors fall into at least two major classes: those applying the Radon transform and those employing linear algebraic matrix inversion. In this paper we apply one of the latter, the “weighted, damped, least squares” technique of stochastic inversion, to two simulated but realistic data sets. This method, which repeatedly has been applied successfully to ocean acoustic tomography, is particularly suited to solving inverse problems in geophysics because it provides an orderly mechanism for judicious use of a priori or external information to complement sparse or nonuniform path integral data. The limited range of angles through which the ionosphere may be viewed on satellite‐to‐ground paths represents such a nonuniformity in ionospheric tomography. The method also provides means for estimating uncertainty in the image field, uncertainty which itself is nonuniform.
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