[en] This document is the final report concluding the execution of the AtMonSat project co-funded by the European Space Agency (ESA) under the Open Space Innovation Platform (OSIP) and the University of Luxembourg. AtMonSat concerns on-board fault detection using artificial neural networks for CubeSat systems and related spacecraft where computing resources are limited. In particular, the concrete problem scenario of malfunctioning of CubeSat board elements is considered. The AtMonSat final report provides the problem statement, discusses the performed experiments designed to generate proper sets of data, and presents the details of the proposed solution. The report shows the devised framework to be both effective and suitable for implementation on a CubeSat.
Disciplines :
Sciences informatiques Ingénierie aérospatiale
Auteur, co-auteur :
HORNE, Ross James ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
MAUW, Sjouke ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
MIZERA, Andrzej ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
STEMPER, André ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
THOEMEL, Jan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Remote Sensing
Langue du document :
Anglais
Titre :
Autonomous Trustworthy Monitoring and Diagnosis of CubeSat Health (AtMonSat)
Date de publication/diffusion :
17 novembre 2022
Maison d'édition :
European Space Agency
Focus Area :
Computational Sciences
Intitulé du projet de recherche :
Autonomous Trustworthy Monitoring and Diagnosis of CubeSat Health (AtMonSat)