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.
KeywordsAirborne gravimetry airborne gravity data processing regional gravity field analysis frequency-dependent weighting
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