Lidar-Basd Estimation of Rotation State for Small Body Rendezvous

This paper explores the potential of flash-Lidar for rotation motion estimation in deep space applications, particularly its capability to navigate and perform maneuvers around small-body asteroids. Building upon a model registration algorithm, we first employ a weighted and scaled Iterative Closest Point (ICP) algorithm to align the Lidar point cloud data with the target terrain model, enabling the calculation of the target's relative pose. Subsequently, we utilize rigid body dynamics theory to determine the absolute angular velocity and axis of rotation of the target. Through simulations, we assess the impact of varying angular velocity magnitudes and Lidar noise levels on the estimation of the target's rotational state. The findings indicate that the proposed approach effectively enhances motion estimation accuracy, paving the way for improved navigation in challenging deep space environments.