(7)ADS-B Identified Routes and Corridors for Recognizing Anomalies From Training Artificial Intelligence (AIRCRAFT.AI)

Air Traffic Management (ATM) modernization and the integration of unmanned aerial systems (UAS) on a global scale signals that the Navy will have to operate in an increasingly dynamic and loaded airspace. To satisfy air traffic authorities emerging performance requirements, airspace users necessarily have to periodically report their positions using Automatic Dependence Surveillance Broadcast (ADS-B), among other technologies. Satellite-based and crowd-sourced monitoring services provide the most complete and timely picture of the global airspace. While tools exist to visualize both current and historic snapshots-in-time, technologies that reveal air traffic patterns across time and space are confined to single-purpose, offline academic or artistic efforts.This SBIR proposes a tool intended for online use to explicitly track, summarize, and visualize airspace utilization over time by processing position reports through state-of-the-art data analytics techniques. A complementary tool can then highlight notable deviations from the learned nominal aircraft behavior. Together these tools will provide a high-level, robust picture of the airspace and flag anomalies that may result from procedural violations, emergent equipment failure, or mal-intent. By utilizing open source, cross-platform tools for development, we will ensure a wide range of transition opportunities to a variety of airspace concerns in Phase III.