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.
@article{arxiv.2305.07333,
title = {Simultaneous navigation and mascon gravity estimation around small bodies},
author = {Julio C. Sanchez and Hanspeter Schaub},
journal= {arXiv preprint arXiv:2305.07333},
year = {2023}
}