Regional gravity field modeling by radially optimized point masses: Case studies with synthetic data

Abstract

A two-step point mass method with free depths is presented for regional gravity field modeling based on the remove-compute-restore 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 system in the least-squares sense. 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.