European Space Agency Benchmark for Anomaly Detection in Satellite Telemetry

Krzysztof Kotowski, Christoph Haskamp, Jacek Andrzejewski, Bogdan Ruszczak, Jakub Nalepa, Daniel Lakey, Peter Collins, Aybike Kolmas, Mauro Bartesaghi, Jose Martinez-Heras, Gabriele De Canio·June 25, 2024

Summary

The ESA-ADB is a standardized satellite telemetry anomaly detection benchmark by the European Space Agency, addressing the lack of such resources in spacecraft operations. It provides a large, curated dataset from three missions for deep learning and AI research, with manual annotations and a tailored evaluation pipeline. The benchmark aims to enhance anomaly detection for better spacecraft monitoring, safety, and maintenance, fostering collaboration among space agencies. Various algorithms, including physics-informed neural networks and deep learning models, have been evaluated, highlighting the need for adaptability to satellite-specific challenges and real-time data processing. The Telemanom algorithm, though relatively slower, demonstrates efficient retraining on OPS-SAT with its simplicity, while more complex methods face memory and performance issues. The overall focus is on improving anomaly detection methods while accounting for the unique characteristics of satellite telemetry data.

Key findings

Paper digest

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Tables

Introduction

Background

Lack of standardized anomaly detection resources

Importance of satellite operations monitoring

Objective

Standardize and enhance anomaly detection

Collaboration among space agencies

Better spacecraft monitoring, safety, and maintenance

Methodology

Data Collection

Three mission datasets

Curated and diverse satellite telemetry data

Data Preprocessing

Manual annotations for ground truth

Adaptation to satellite-specific challenges

Algorithms and Evaluation

Physics-Informed Neural Networks (PINNs)

Modeling physical principles

Challenges and limitations

Deep Learning Models

Performance and memory issues

Real-time data processing requirements

Telemanom Algorithm

Efficient retraining on OPS-SAT

Simplicity and adaptability

Research Focus

Improving anomaly detection methods

Accounting for unique telemetry data characteristics

Balancing performance and adaptability

Basic info

papers

machine learning

artificial intelligence

Advanced features

Insights

Which organization developed the ESA-ADB, and why was it created?

What kind of data does the ESA-ADB provide for researchers?

What is the ESA-ADB primarily designed for?

How does the benchmark aim to benefit spacecraft operations through anomaly detection?