A review of anomaly detection in spacecraft telemetry data
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| Title: | A review of anomaly detection in spacecraft telemetry data |
|---|---|
| Authors: | Fejjari, Asma, Delavault, Alexis, Camilleri, Robert, Valentino, Gianluca |
| Publisher Information: | MDPI AG |
| Publication Year: | 2025 |
| Collection: | University of Malta: OAR@UM / L-Università ta' Malta |
| Subject Terms: | Aerospace telemetry, Space vehicles -- Equipment and supplies, Aerospace engineering -- Data processing, Artificial intelligence -- Industrial applications, Fault location (Engineering) -- Data processing |
| Description: | Telemetry data play a pivotal role in ensuring the success of spacecraft missions and safeguarding the integrity of spacecraft systems. Therefore, the timely detection and subsequent notification of any abnormal events related to the functionality of spacecraft subsystems are crucial to ensure their safe operation. In recent years, several anomaly detection methods have been developed to monitor spacecraft telemetry data and detect anomalies. This manuscript provides a comprehensive literature review of the existing anomaly detection methods for spacecraft telemetry data. It exposes the challenges faced by such systems, highlights the strengths and limitations of each anomaly detection method, and assesses and compares the performance of these approaches in detecting anomalies. Initial results show that GCN and TCN models have achieved promising precision up to 94%. The paper concludes with a series of recommendations and the potential research directions. ; peer-reviewed |
| Document Type: | article in journal/newspaper |
| Language: | English |
| Relation: | Fejjari, A., Delavault, A., Camilleri, R., & Valentino, G. (2025). A Review of Anomaly Detection in Spacecraft Telemetry Data. Applied Sciences, 15(10), 5653.; https://www.um.edu.mt/library/oar/handle/123456789/137381 |
| DOI: | 10.3390/app15105653 |
| Availability: | https://www.um.edu.mt/library/oar/handle/123456789/137381 https://doi.org/10.3390/app15105653 |
| Rights: | info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder |
| Accession Number: | edsbas.5E4C0CFE |
| Database: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | Telemetry data play a pivotal role in ensuring the success of spacecraft missions and safeguarding the integrity of spacecraft systems. Therefore, the timely detection and subsequent notification of any abnormal events related to the functionality of spacecraft subsystems are crucial to ensure their safe operation. In recent years, several anomaly detection methods have been developed to monitor spacecraft telemetry data and detect anomalies. This manuscript provides a comprehensive literature review of the existing anomaly detection methods for spacecraft telemetry data. It exposes the challenges faced by such systems, highlights the strengths and limitations of each anomaly detection method, and assesses and compares the performance of these approaches in detecting anomalies. Initial results show that GCN and TCN models have achieved promising precision up to 94%. The paper concludes with a series of recommendations and the potential research directions. ; peer-reviewed |
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| DOI: | 10.3390/app15105653 |