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Bayesian Estimation of Surface Information from Radar Images

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.

Identiferoai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:open_access_dissertations-1364
Date01 May 1993
CreatorsHartt, Keith David
PublisherScholarWorks@UMass Amherst
Source SetsUniversity of Massachusetts, Amherst
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceOpen Access Dissertations

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