A new strategy for processing airborne gravity data

We present a new approach for regional gravity field analysis from airborne gravity data, which combines separate processing steps into one inversion scheme. The approach uses a spectral representation of the Earth’s gravity field in terms of a series of harmonic base functions, expressed in a local Cartesian reference frame. The parameters of this representation are estimated using least-squares techniques. Special emphasis is put on the proper modeling of data noise. Frequency-dependent data weighting is applied to handle colored noise, which replaces the traditional method of low-pass filtering and crossover adjustment. To suppress model errors at the highest spatial frequencies, first-order Tikhonov regularization is applied. The performance of the developed technique is assessed for the inversion of gravity disturbances into the disturbing potential, using simulated data.