LAUSR

Abstract Future Active Debris Removal missions will require an autonomous spacecraft (chaser) to safely monitor at close distance, and then approach and dispose an inactive artificial space object (target). Since these targets are uncooperative, meaning that they cannot provide any hint or help to the chaser navigation system, such operations require the target-chaser relative state and the target inertia parameters to be accurately estimated relying only on measurements from active or passive Electro-Optical sensors. In this framework, this paper proposes an original multi-step architecture for the estimation of the relative motion and inertia parameters of an uncooperative target during a close-range monitoring trajectory. In the first phase, LIDAR-based pose measurements and a smoothing approach are used to retrieve accurate, linearly independent estimates of the target angular velocity. These estimates are then used to compute the target's moments of inertia ratios solving a linear system based on the conservation equation for the angular momentum. Once the inertia parameters are accurately estimated, the LIDAR-based pose measurements are used to feed an Unscented Kalman Filter to determine the full relative state according to a loosely coupled configuration. The architecture foresees autonomous failure detection strategies to avoid divergence in the relative state estimation error caused by unavoidable, unfavorable target observation conditions occurring during the monitoring trajectory. Performance assessment is carried out through numerical simulations realistically reproducing close-range relative motion dynamics and LIDAR sensor operation, and considering targets characterized by highly variable size, shape, and orbital dynamics as test cases.