Durga addresses the Air Forces need for Autonomous Satellite Ground Operations using a mature suite of software methods that detect and respond to anomalies in streams of data, both in real time and over history. In addition to detecting rapid spikes or gradual drifts in telemetry data, Durgas methods can discover periodic and seasonal patterns, as well as connections between data features that can assist operators in diagnosing and handling complex non-deterministic scenarios. These analytics, collectively called the Cognitive Engine, are powered by new advances in Artificial Intelligence and Machine Learning, and they form the core of a complete system architecture that also defines methods for data acquisition and storage according to a uniform data model, and standards for data visualization and user interaction. The architecture enables the system to scale in data volume and velocity from an initial prototype in a single Space Operations Center to a global system-of-systems deployment, and it provides a pathway for incremental growth in complexity by adding new features into the data space and by adding new algorithms to the Cognitive Engine. The full Durga architecture also contains a powerful condition-action Rules Engine that enables expert users to create deterministic responses to specific events.
