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Method of surface topography retrieval by direct solution of sparse weighted seminormal equations
Jeffrey Koskulics1, Steven Englehardt, Steven Long
1Stevens Institute of Technology, Hoboken, New Jersey 07030, USA. jkoskuli@stevens.edu
Abstract:
A new method is presented to estimate the topography of a rough surface. A formulation is provided in which immediate measurements and a priori observations of surface elevation, slope and curvature, are considered simultaneously as a linear algebraic system of finite difference equations. Least squares solutions are computed directly by sparse orthogonal-triangular (QR) factorization of the weighted seminormal equations, an approach made practical for large systems with powerful computational hardware and algorithms that have become available recently. Retrievals are demonstrated from synthetic slope data and from measurements of slope on a rough water surface. The method provides a general approach to retrieving topography from measurements of elevation, slope and curvature.
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