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The heterogeneity of the small body population complicates the prediction ofsmall body properties before the spacecraft's arrival. In the context ofautonomous small body exploration, it is crucial to develop algorithms thatestimate the small body characteristics before orbit insertion and closeproximity operations. This paper develops a vision-based estimation of thesmall-body rotational state (i.e., the center of rotation and rotation axisdirection) during the approach phase. In this mission phase, the spacecraftobserves the rotating celestial body and tracks features in images. As featuretracks are the projection of the landmarks' circular movement, the possiblerotation axes are computed. Then, the rotation axis solution is chosen amongthe possible candidates by exploiting feature motion and a heuristic approach.Finally, the center of rotation is estimated from the center of brightness. Thealgorithm is tested on more than 800 test cases with two different asteroids(i.e., Bennu and Itokawa), three different lighting conditions, and more than100 different rotation axis orientations. Each test case is composed of about250 synthetic images of the asteroid which are used to track features anddetermine the rotational state. Results show that the error between the truerotation axis and its estimation is below $10^{\circ}$ for $80\%$ of theconsidered test cases, implying that the proposed algorithm is a suitablemethod for autonomous small body characterization.

Vision-Based Estimation of Small Body Rotational State during the Approach Phase