As spacecraft missions become more complex and ambitious, it becomes increasingly
important to track the status and health of the spacecraft in real-time to ensure mission …

Despite the dominance of unsupervised and self-supervised anomaly detection methods in
the current satellite fault diagnosis domain, supervised anomaly detection offers a superior …

Anomalies frequently occur during the operation of spacecraft in orbit, and studying anomaly
detection methods is crucial to ensure the normal operation of spacecraft. Due to the …

The detection and segmentation of key spacecraft components is a crucial prerequisite for
the successful execution of on-orbit capture tasks; however, the existing spacecraft datasets …

To enhance the accuracy of deep learning methods based on reconstruction discrepancy in
satellite anomaly detection tasks, this study proposes a dual-branch reconstruction model …

Data-driven methodologies are indispensable for early satellite anomaly detection.
However, their effectiveness in capturing temporal dependencies within non-stationary …

The unique challenges posed by the space environment, characterized by extreme
conditions and limited accessibility, raise the need for robust and reliable techniques to …

Anomaly detection in spacecraft plays a pivotal role in ensuring the safety and reliability of
aerospace missions. As contemporary spacecraft systems become intricate with the …

Traditional correlation and causality analyses based on telemetry data often lack depth in
analyzing the multi-level coupling of faults and their emergent effects in spacecraft. Large …

As spacecraft missions become more complex and ambitious, it becomes increasingly
important to track the status and health of the spacecraft in real-time to ensure mission …