A sparse spectrum technique for gridding and separating potential field anomalies

Abstract

The discrete Fourier transform of a potential field, measured at stations irregularly distributed on a surface, is modeled by means of a high-resolution sparse estimate derived originally for seismic signal processing. The coefficients of this estimate produce a model with only few components having a significant value. A steepest-descent algorithm gives a computing alternative to large matrix multiplications and inversions.