Telemetry Anomaly Detection System using Machine Learning to Streamline Mission Operations

Spacecraft housekeeping telemetry is monitored at
flight control centers by the operations engineers using tools
that can perform limit checking or simple trend analysis.
Recent developments in machine learning techniques for
anomaly detection enables the implementation of more
sophisticated systems that aim to augment current state-of-theart
mission tools to provide valuable decision support for the
spacecraft operators, assisting in anomaly detection and
potentially saving console time for the engineers. We will
show some results of the implementation of an anomaly
detection tool for the NASA Mars Science Laboratory
mission.