Automated False Track Identification

Suboptimized real-time surveillance systems trade off reporting all targets in the surveillance volume against minimizing the number of false tracks. Analysis of archived data can identify false tracks. By automating the analysis, system optimization can be done sooner. Automated analysis identifies candidate false tracks using track characteristics over the life of the track. These characteristics depend on the sensor data and operational environment. This paper discusses automated false track identification of ASDE-X (Airport Surface Detection Equipment Model X ) tracks collected at multiple airports. These tracks are supported by radar and multilateration sensor data.