Abstract: Affected by factors of measurement errors and so on,the surface mass variation inversion results would be dominated by serious north-to-south stripe noise with using time-variable gravity models directly. Filtering methods must be adopted. Optimal parameters of different filtering methods are determined by taking signal-to-noise ratio maximum as the criterion. On this basis, a new non-isotropic combination filtering method is proposed based on the features of time-variable gravity model spherical harmonic serrors. The new non-isotropic combination filtering method is different from traditional two-steps combination filtering methods. It just performs in one step with combining non-isotropic Gaussian filtering and RMS filtering. The basic idea of the new combination filtering method is to apply larger weights to low-order spherical harmonic coefficients while smaller weights to high-order spherical harmonic coefficients for keeping more signals and suppressing noise. The experiment results show that the new combination filtering method is simple to calculate and stripe noise can be removed effectively. The new combination filtering method improves the signal-to-noise ratio compared with previous filtering methods and traditional two-steps combination filtering methods.

Key words: combination filtering, stripe noise, non-isotropic gaussian filtering, root mean square filtering, signal-to-noise ratio