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arXiv · 2605.06681

A Hierarchical Ensemble Pipeline for Anomaly Detection in ESA Satellite Telemetry

Lorenzo Riccardo Allegrini·Geremia Pompei
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Abstract

A hierarchical ensemble pipeline is introduced to address anomaly detection in multivariate telemetry data provided by European Space Agency (ESA). The method integrates shapelet-based and statistical feature extraction, per-channel modeling, intra-channel stacking, and a final cross-channel aggregation. The pipeline is trained and validated using time-series cross-validation and two-level masking strategies to prevent information leakage. Results on the European Space Agency Anomaly Detection Benchmark (ESA-ADB) challenge demonstrate strong generalization, highlighting the effectiveness of hierarchical modeling in detecting subtle anomalies in realistic satellite telemetry.

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Lorenzo Riccardo Allegrini, Geremia Pompei. 2026-04-22. A Hierarchical Ensemble Pipeline for Anomaly Detection in ESA Satellite Telemetry. https://doi.org/10.1007/978-3-032-19105-2_7

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