Surveillance technologies play an important role in civil aviation safety by providing situational awareness to air traffic controllers and pilots. Tens of thousands of aircrafts operate daily, and each one of them needs to be tracked by combining data from several data sources including ADS-B and radar data for maintaining the safety of airspace. These heterogeneous data sources are aggregated together with schedule and flight status data from airlines and airports. This aggregate data is used to provide appropriate flight tracking of individual aircrafts and helps ensuring that the air traffic operates with maximum safety and minimum delays. This is achieved by a complex system of command centers, control towers, radar ground stations, and automated surveillance equipment. As air travel grows each year, global aviation safety continues to improve thanks to these sophisticated systems. Yet, it is unrealistic to expect that the system would detect, identify and respond to all flight anomalies. As was the case in Germanwings flight 9525, the flight anomalies that are not detected in time may result in catastrophes. This paper analyzes the unfortunate case of Germanwings flight 9525 and proposes an automated flight anomaly detection technology to improve situational awareness for air traffic controllers and pilots, and enhance aviation safety.
How to Cite
Data-driven detection methodologies, flight anomalies
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