Applications of Deep Learning Neural Networks to Satellite Telemetry Monitoring

Abstract

As part of the Automated Telemetry Health Monitoring System (ATHMoS) being developed at GSOC, we performed an investigation into potential applications of artificial neural networks to our existing health monitoring system. In the end, we have created an experimental module which uses several deep learning neural networks to augment our existing data analysis algorithms. The module accomplishes three things; automatic feature extraction, anomaly detection, and telemetry prediction. Automatic feature extraction is used to determine numerical values which represent a time window of a single parameters telemetry data, then, using these abstract numeric values we augment our existing so-called feature vectors used in our ATHMoS anomaly detection system to provide additional information in the anomaly detection.