http://arxiv.org/abs/2305.07333
This manuscript develops a simultaneous navigation and gravity estimation strategy around a small body. The scheme combines dynamical model compensation with a mascon gravity fit. Dynamical compensation adds the unmodeled acceleration to the filter state. Consequently, the navigation filter is able to generate an on-orbit position-unmodeled acceleration dataset. The available measurements correspond to the landmarks-based navigation technique. Accordingly, an on-board camera is able to provide landmark pixels. The aforementioned position-unmodeled acceleration dataset serves to train a mascon gravity model on-board while in flight. The training algorithm finds the optimal mass values and locations using Adam gradient descent. By a careful choice of the mascon variables and constraints projection, the masses are ensured to be positive and within the small body shape. The numerical results provide a comprehensive analysis on the global gravity accuracy for different estimation scenarios.
J. Sanchez and H. Schaub
Mon, 15 May 23
5/53
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