The objective of this Ph.D. thesis is the design, development and performance assessment of innovative Guidance Navigation and Control techniques enabling the autonomous execution of complex tasks required by future space missions, such as the close proximity maneuvering of a chaser spacecraft around a resident space object and the controlled de-orbiting of micro-satellite by means of aerodynamic drag. Regarding close-proximity operations, both Active Debris Removal and In-Orbit Servicing missions requires an autonomous spacecraft (chaser) to safely monitor and then approach an active/inactive artificial space object (target) which may be or not equipped with artificial markers to aid the relative navigation task. In this framework, this thesis proposes two original relative navigation architecture to be applied in the monitoring and close-approach phase of an ADR/IOS mission. For the monitoring phase, an original multi-step architecture for the estimation of both relative motion parameters and inertia parameters of an uncooperative space target is proposed. Once the position and attitude (pose) parameters are initialized (first step), 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 moment 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 a Kalman Filter to determine the full relative state according to a loosely coupled configuration. In the final approach phase, when the chaser has to capture the target by means of a robotic arm, a second EO sensor (TOF camera) is installed on the tip of the end-effector in order to get direct pose measurements of the end effector with respect to the selected grasping point. The measurements of the two EO-sensors are integrated within two different Kalman Filters aimed ...
GNC Technologies and Algorithms for Close-Proximity Flight and Re-entry Applications
2023-03-10
Nocerino, Alessia (2023) GNC Technologies and Algorithms for Close-Proximity Flight and Re-entry Applications. [Tesi di dottorato]
Theses
Electronic Resource
Italian , English