GRAIL Gravity Field Determination Using the Celestial Mechanics Approach - Status Report

Wednesday, 17 December 2014
Stefano Bertone1, Daniel Arnold2, Adrian Jaeggi1, Gerhard Beutler3, Heike Bock1, Ulrich Meyer1 and Leos Mervart4, (1)University of Bern, Bern, Switzerland, (2)University of Bern, Berne, Switzerland, (3)Astronomical Institute, Bern, Switzerland, (4)Czech Technical University in Prague, Prague, Czech Republic
The NASA mission GRAIL (Gravity Recovery And Interior Laboratory) inherits its concept from the GRACE (Gravity Recovery And Climate Experiment) mission to determine the gravity field of the Moon. The use of inter-satellite Ka-band range-rate (KBRR) observations enables data aquisition even when the spacecraft are not tracked from the Earth. The data allows for a highly accurate estimation of the lunar gravity field on both sides of the Moon, which is crucial to improve the understanding of its internal structure and thermal evolution. In this presentation we discuss GRAIL-based lunar gravity fields generated with the Celestial Mechanics Approach using the Bernese Software. Currently KBRR observations and position data (GNI1B products) are used to solve for the lunar gravity field parameters in a generalized orbit determination problem. Apart from normalized spherical harmonic coefficients up to degree n = 200, also arc-specific parameters like initial state vectors and empirical parameters (pseudo-stochastic pulses or piecewise constant accelerations) are set up as common parameters for all measurement types. The latter shall compensate for imperfect models of non-gravitational accelerations, e.g., caused by solar radiation pressure. We compare our results from the nominal and from the extended mission phase with the official level 4 gravity field models released in April 2014. As a further extension of our processing the GNI1B positions are replaced by the original Doppler observations of the Deep Space Network (DSN) to allow for a completely independent determination of the lunar gravity field using the Celestial Mechanics Approach and we present the currently achieved status of the DSN data modeling in the Bernese Software.