Airborne Scalar Gravimetry for Regional Gravity Field Mapping and Geoid Determination

Airborne gravimetry has during the last decade become a really operational way to map the Earths gravity field, mainly because of improvements in GPS technology. Improved inertial sensors have been employed for airborne gravity recovery during the last few years and show some promising results, but the far biggest volume of airborne gravity mapping are done with spring type gravimeters mounted on stabilized platforms, even this sensor technology is quite old. This paper addresses possible improvements in the processing of airborne gravimetry from such a spring type gravimeter system. One of the biggest advantages of the spring type gravimeter compared to inertial sensors is its superior long-term stability. A new algorithm to correct for platform off-leveling errors is derived and it is shown that this new algorithm in combination with the good drift characteristic for the spring type gravimeter yields virtual bias free data. This is an important point when it comes to geodetic use of the acquired data. The near bias free nature of the data from our system is underlined by the fact that no crossover adjustment procedures are involved in the data reduction. Also routines to identify and correct for some GPS related errors are outlined. Unfiltered gravity estimates have proven to be a good indicator for artifact accelerations coming from GPS ambiguity fixing problems, especially under smooth flight conditions. The resolution of the airborne gravity system is optimized through an analysis of the vertical sensor response. Concepts as apparent K-factor and filter-optimized K-factor are introduced in order to access the combined response of the gravimeter beam and the GPS positioning system. It is shown that the analyzed system maps gravity with an accuracy of 1.3 mgal at 6 km resolution. This performance may degrade during periods with air turbulence. The noise estimates for four consecutive years of airborne measurements in Greenland ranged from 1.3 to 2.0 mgal. It should be noticed that 6 km is a conservative estimate for the resolution. The filter can under low-turbulent conditions be shortened considerably and still yield virtual the same data accuracy.

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