Analytical methods of multi-source gravity data fusion processing in the sea area

Nowadays, extensive marine gravity measurements, airborne gravity measurements and satellite gravity data exist for sea areas, and can be combined to build a precise digital gravity model. Based on a brief analysis of multi-source gravity data characteristics, we propose two new analytical methods for optimal combination of the marine, airborne and satellite gravity data. The first new method is called one-step fusion processing, in which an interpolation model is used to grid the multi-source gravity data with a double weight factor. The other new method is called multi-step fusion processing, in which the data management procedure is modified to a four step process based on the theories of adjustment, filtering, prediction and interpolation. When compared to the traditional statistical methods, such as Least Square Collocation, using these two new approaches can simplify data fusion procedures, with stabile and reliable computation results. Finally, a practical marine gravity measurement and a satellite gravity data set are used as a case study to demonstrate the efficiency of these proposed analytical data fusion processing methods.