@article{PAR00007472,
  title = {{D}enoising satellite gravity signals by independent component analysis},
  author = {{F}rappart, {F}. and {R}amillien, {G}. and {M}aisongrande, {P}. and {B}onnet, {M}arie-{P}aule},
  editor = {},
  language = {{ENG}},
  abstract = {{I}ndependent component analysis ({ICA}) is a blind separation method based on simple assumptions of the independence of sources and the non-{G}aussianity of observations. {A}n 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 {G}ravity {R}ecovery and {C}limate {E}xperiment ({GRACE}) satellites. {W}e 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. {T}he efficiency of the methodology is demonstrated on a synthetic case. {A}pplied 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. {T}his technique gives results equivalent to the destriping method for continental water storage.},
  keywords = {{F}iltering technique ; {G}ravimetry from space ; {H}ydrology ; {I}ndependent component analysis ({ICA})},
  booktitle = {},
  journal = {{IEEE} {G}eoscience and {R}emote {S}ensing {L}etters},
  volume = {7},
  numero = {3},
  pages = {421--425},
  year = {2010},
  DOI = {10.1109/{LGRS}.2009.2037837},
  URL = {https://www.documentation.ird.fr/hor/{PAR}00007472},
}