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Bayesian Estimation of Surface Information from Radar Images

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Abstract
The dissertation presents a method for deriving the shape of a surface from a radar image of the surface. An appropriate model of radar image formation is derived from physical principles. A Bayesian formulation of the inversion problem is developed upon which a computational strategy is based. Theoretical results on random surfaces relevant to the prior distribution are presented, and convergence and optimality properties of a new sampling algorithm are described. The technique is applied to Magellan data of Venus.
Type
Dissertation (Open Access)
Date
1993-05
Publisher
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