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Space-wise approach for airborne gravity data modelling / Daniele Sampietro in Journal of geodesy, vol 91 n° 5 (May 2017)  

Public [article]  inJournal of geodesy > vol 91 n° 5 (May 2017) . - pp 535 – 545 Titre : Space-wise approach for airborne gravity data modelling Type de document : Article/Communication Auteurs : Daniele Sampietro, Auteur ; M. Cappon, Auteur ; A. H. Mansi, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 535 – 545 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] collocation par moindres carrés [Termes IGN] covariance [Termes IGN] filtre de Wiener [Termes IGN] géoïde gravimétrique [Termes IGN] gravimétrie aérienne [Termes IGN] modèle de géopotentiel Résumé : (auteur) Regional gravity field modelling by means of remove-compute-restore procedure is nowadays widely applied in different contexts: it is the most used technique for regional gravimetric geoid determination, and it is also used in exploration geophysics to predict grids of gravity anomalies (Bouguer, free-air, isostatic, etc.), which are useful to understand and map geological structures in a specific region. Considering this last application, due to the required accuracy and resolution, airborne gravity observations are usually adopted. However, due to the relatively high acquisition velocity, presence of atmospheric turbulence, aircraft vibration, instrumental drift, etc., airborne data are usually contaminated by a very high observation error. For this reason, a proper procedure to filter the raw observations in both the low and high frequencies should be applied to recover valuable information. In this work, a software to filter and grid raw airborne observations is presented: the proposed solution consists in a combination of an along-track Wiener filter and a classical Least Squares Collocation technique. Basically, the proposed procedure is an adaptation to airborne gravimetry of the Space-Wise approach, developed by Politecnico di Milano to process data coming from the ESA satellite mission GOCE. Among the main differences with respect to the satellite application of this approach, there is the fact that, while in processing GOCE data the stochastic characteristics of the observation error can be considered a-priori well known, in airborne gravimetry, due to the complex environment in which the observations are acquired, these characteristics are unknown and should be retrieved from the dataset itself. The presented solution is suited for airborne data analysis in order to be able to quickly filter and grid gravity observations in an easy way. Some innovative theoretical aspects focusing in particular on the theoretical covariance modelling are presented too. In the end, the goodness of the procedure is evaluated by means of a test on real data retrieving the gravitational signal with a predicted accuracy of about 0.4 mGal. Numéro de notice : A2017-227 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0981-y Date de publication en ligne : 18/12/2016 En ligne : https://doi.org/10.1007/s00190-016-0981-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85108 [article]