Article (Scientific journals)
Anomaly Detection Using Deep Learning Respecting the Resources on Board a CubeSat
HORNE, Ross James; MAUW, Sjouke; MIZERA, Andrzej et al.
2023In Journal of Aerospace Information Systems, p. 1-14
Peer reviewed
 

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Keywords :
Electrical and Electronic Engineering; Computer Science Applications; Aerospace Engineering
Abstract :
[en] We explore the feasibility of onboard anomaly detection using artificial neural networks for CubeSat systems and related spacecraft where computing resources are limited. We gather data for training and evaluation using a CubeSat in a laboratory for a scenario where a malfunctioning component affects temperature fluctuations across the control system. This data, published in an open repository, guides the selection of suitable features, neural network architecture, and metrics comprising our anomaly detection algorithm. The precision and recall of the algorithm demonstrate improvements as compared to out-of-limit methods, whereas our open-source implementation for a typical microcontroller exhibits small memory overhead, and hence may coexist with existing control software without introducing new hardware. These features make our solution feasible to deploy on board a CubeSat, and thus on other, more advanced types of satellites.
Disciplines :
Aerospace & aeronautics engineering
Author, co-author :
HORNE, Ross James ;  University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Computer Science > Team Sjouke MAUW
MAUW, Sjouke ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
MIZERA, Andrzej  ;  University of Luxembourg ; IDEAS-NCBR, Chmielna 69, 00-801 Warsaw, Poland
Stemper, André;  University of Luxembourg, L-4365 Esch-sur-Alzette, Grand Duchy of Luxembourg
THOEMEL, Jan  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPASYS
External co-authors :
no
Language :
English
Title :
Anomaly Detection Using Deep Learning Respecting the Resources on Board a CubeSat
Publication date :
25 August 2023
Journal title :
Journal of Aerospace Information Systems
eISSN :
2327-3097
Publisher :
American Institute of Aeronautics and Astronautics (AIAA)
Pages :
1-14
Peer reviewed :
Peer reviewed
Funders :
Université du Luxembourg
European Space Agency
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since 24 October 2023

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