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IAG 150 Years pp 233-239 | Cite as

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

  • Miao LinEmail author
  • Heiner Denker
  • Jürgen Müller
Conference paper
First Online:
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Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 143)

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.

Keywords

Free depths Least-squares collocation Point mass method Regional gravity field modeling Tikhonov regularization 
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Notes

Acknowledgements

Three anonymous reviewers are acknowledged for their valuable comments which improved the original manuscript. The first author is financially supported by China Scholarship Council (CSC) for his PhD study in Germany.

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© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Institut für Erdmessung (IfE), Leibniz Universität HannoverHannoverGermany

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