The exponential increase of the needs of people in the modern society and the contextual development of the space technologies have led to a significant use of the lower Earth’s orbits for placing artificial satellites. The current overpopulation of these orbits also increased the interest of the major space agencies in technologies for the removal of at least the biggest spacecraft that have reached their end-life or have failed their mission. One of the key functionalities required in a mission for removing a non-cooperative spacecraft is the assessment of its kinematics and inertial properties. In a few cases, this information can be approximated by ground observations. However, a re-assessment after the rendezvous phase is of critical importance for refining the capture strategies preventing accidents. The CADET program (CApture and DE-orbiting Technologies), funded by Regione Piemonte and led by Aviospace s.r.l., involved Politecnico di Torino in the research for solutions to the above issue. This dissertation proposes methods and algorithms for estimating the location of the center of mass, the angular rate, and the moments of inertia of a passive object. These methods require that the chaser spacecraft be capable of tracking several features of the target through passive vision sensors. Because of harsh lighting conditions in the space environment, feature-based methods should tolerate temporary failures in detecting features. The principal works on this topic do not consider this important aspect, making it a characteristic trait of the proposed methods. Compared to typical v treatments of the estimation problem, the proposed techniques do not depend solely on state observers. However, methods for recovering missing information, like compressive sampling techniques, are used for preprocessing input data to support the efficient usage of state observers. Simulation results showed accuracy properties that are comparable to those of the best-known methods already proposed in the literature. The developed algorithms were tested in the laboratory staged by Aviospace s.r.l., whose name is CADETLab. The results of the experimental tests suggested the practical applicability of such algorithms for supporting a real active removal mission.

Fault-tolerant feature-based estimation of space debris motion and inertial properties / Biondi, Gabriele. - (2017). [10.6092/polito/porto/2674900]

Fault-tolerant feature-based estimation of space debris motion and inertial properties

BIONDI, GABRIELE
2017

Abstract

The exponential increase of the needs of people in the modern society and the contextual development of the space technologies have led to a significant use of the lower Earth’s orbits for placing artificial satellites. The current overpopulation of these orbits also increased the interest of the major space agencies in technologies for the removal of at least the biggest spacecraft that have reached their end-life or have failed their mission. One of the key functionalities required in a mission for removing a non-cooperative spacecraft is the assessment of its kinematics and inertial properties. In a few cases, this information can be approximated by ground observations. However, a re-assessment after the rendezvous phase is of critical importance for refining the capture strategies preventing accidents. The CADET program (CApture and DE-orbiting Technologies), funded by Regione Piemonte and led by Aviospace s.r.l., involved Politecnico di Torino in the research for solutions to the above issue. This dissertation proposes methods and algorithms for estimating the location of the center of mass, the angular rate, and the moments of inertia of a passive object. These methods require that the chaser spacecraft be capable of tracking several features of the target through passive vision sensors. Because of harsh lighting conditions in the space environment, feature-based methods should tolerate temporary failures in detecting features. The principal works on this topic do not consider this important aspect, making it a characteristic trait of the proposed methods. Compared to typical v treatments of the estimation problem, the proposed techniques do not depend solely on state observers. However, methods for recovering missing information, like compressive sampling techniques, are used for preprocessing input data to support the efficient usage of state observers. Simulation results showed accuracy properties that are comparable to those of the best-known methods already proposed in the literature. The developed algorithms were tested in the laboratory staged by Aviospace s.r.l., whose name is CADETLab. The results of the experimental tests suggested the practical applicability of such algorithms for supporting a real active removal mission.
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2674900
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