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Erschienen in:

2015 | Online First | Buchkapitel

Regional Gravity Field Modeling by Radially Optimized Point Masses: Case Studies with Synthetic Data

verfasst von : Miao Lin, Heiner Denker, Jürgen Müller

Erschienen in: International Association of Geodesy Symposia

Verlag: Springer International Publishing

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Abstract

A two-step point mass method with free depths is presented for regional gravity field modeling based on the remove-compute-restore (RCR) technique. Three numerical test cases were studied using synthetic data with different noise levels. The point masses are searched one by one in the first step with a simultaneous determination of the depth and magnitude by the Quasi-Newton algorithm (L-BFGS-B). In the second step, the magnitudes of all searched point masses are readjusted with known positions by solving a linear least-squares problem. Tikhonov regularization with an identity regularization matrix is employed if ill-posedness exists. One empirical and two heuristic methods for choosing proper regularization parameters are compared. In addition, the solutions computed from standard and regularized least-squares collocation are presented as references.

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Titel: Regional Gravity Field Modeling by Radially Optimized Point Masses: Case Studies with Synthetic Data
verfasst von: Miao Lin
Heiner Denker
Jürgen Müller
Verlag: Springer International Publishing
DOI: https://doi.org/10.1007/1345_2015_92

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