%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture non répertoriées par l'AERES
%A Frappart, F.
%A Ramillien, G.
%A Maisongrande, P.
%A Bonnet, Marie-Paule
%T Denoising satellite gravity signals by independent component analysis
%D 2010
%L PAR00007472
%G ENG
%J IEEE Geoscience and Remote Sensing Letters
%K Filtering technique ; Gravimetry from space ; Hydrology ; Independent component analysis (ICA)
%M HAL:hal-00515381
%N 3
%P 421-425
%R 10.1109/LGRS.2009.2037837
%U https://www.documentation.ird.fr/hor/PAR00007472
%> https://www.documentation.ird.fr/intranet/publi/2023-02/010087326.pdf
%V 7
%W Horizon (IRD)
%X Independent component analysis (ICA) is a blind separation method based on simple assumptions of the independence of sources and the non-Gaussianity of observations. An approach based on ICA is used here to extract hydrological signals over land and oceans from the polluting striping noise due to orbit repetitiveness and present in the gravity anomalies detected by the Gravity Recovery and Climate Experiment (GRACE) satellites. We took advantage of the availability of monthly level-2 GRACE solutions from three official providers (i.e., CSR, JPL, and GFZ) that can be considered as different observations of the same phenomenon. The efficiency of the methodology is demonstrated on a synthetic case. Applied to one month of GRACE solutions, it allows for clearly separating the total water storage change from the meridional-oriented spurious gravity signals on the continents but not on the oceans. This technique gives results equivalent to the destriping method for continental water storage.
%$ 126