LARGE SCALE GEODETIC LEAST SQUARES ADJUSTMENT BY DISSECTION AND ORTHOGONAL DECOMPOSITION Gene
نویسندگان
چکیده
Very large seal@ matrix problems currently arise in the context of accurately computing the coordinates of points on the surface of the earth. Here g.eodesists adjust the approximate values of these coordinates by computing least squares solutions to large sparse systems of equations which result from relating the coordinates to certain observations such as distances or angles between points. The purpose of this paper is to suggest an alternative to the formation and solution of the normal eqgations for these least squares adjustment problems. In particular, it is shown how a block-orthogonal decomposition method can be used in conjunction with a nested dissection scheme to produce an algorithm for solving such ,problems which combines efficient data management with numerical stability. As an indication of the magnitude that these least squares adjustment problems can sometimes attain, the forthcoming readjustment of the North American Datum in 1983 by the National Geodetic Survey is discussed. Here it becomes necessary to linearize and solve an overdetermined system of approximately ~,OOO,OOO equations in 400,000 unknowns a truly large-scale matrix problem.
منابع مشابه
NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer
Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as dissection of molecular pathways of pathophysiological conditions. Here, proton nuclear magnetic ...
متن کاملSparse Gaussian Elimination and Orthogonal Factorization
We consider the solution of a linear system Ax = b on a distributedmemorymachine when the matrixA has full rank and is large, sparse and nonsymmetric. We use our Cartesian nested dissection algorithm to compute a ll-reducingcolumn ordering of the matrix. We develop algorithms that use the associated separator tree to estimate the structure of the factor and to distribute and perform numeric com...
متن کاملDevelopment of Numerical Methods for Geodynamo and Mantle Convection Simulations
2. Development of New Spherical Grid: Yin-Yang Grid Since the finite difference method enables us to make highly optimized programs for massively parallel computers, we exploit the possibility of the finite difference method for simulations in spherical shell geometry with radius r (ri ≤ r ≤ ro), colatitude θ (0 ≤ θ ≤ π), and longitude φ (0 ≤ φ < 2π). Because there is no grid mesh that is ortho...
متن کاملThe Dissection of Five-dimensional Simplices into Orthoschemes
In this paper the dissection of ve-dimensional simplices into or-thoschemes is shown. Firstly, some general methods for dissecting n-dimensional Euclidean simplices are described. For this, a description of simplices by graphs is given. All methods for cutting a simplex are investgated with the help of these graphs. The dissection of the ve-dimensional Euclidean simplices is thoroughly investig...
متن کاملSparse Gaussian Elimination Andorthogonal
We consider the solution of a linear system Ax = b on a distributed memory machine when the matrix A has full rank and is large, sparse and nonsymmetric. We use our Cartesian nested dissection algorithm to compute a ll-reducingcolumn ordering of the matrix. We develop algorithms that use the associated separator tree to estimate the structure of the factor and to distribute and perform numeric ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1998