Fusion of airborne radar and FLIR sensors for runway incursion detection

Objects on the runway are a leading cause of accidents to landing aircraft. A recent study by RTI for NASA investigated the detection of those objects from the aircraft using sensors commonly found on commercial aircraft: infrared cameras and weather radar. Attention was given to sensor enhancements that would improve the probability of detection, followed by the development of detection routines for each sensor. Finally a fusion process was developed based on a tracking system. A laboratory-based demonstration fusion system has been developed for the detection of runway incursions. This system uses FLIR data recorded from an aircraft on approach including long-wave and short-wave infrared video, aircraft navigation data from NASA flight tests, and simulated radar data based on the flight test parameters. The radar data are obtained from an updated NASA/RTI-developed Airborne Doppler Weather Radar Simulation (ADWRS) program. This paper describes the fusion process and presents initial results of system performance under clear weather night conditions. We show how the FLIR processor effectively extracts targets of opportunity from the infrared imagery. The LWIR provides good target detection capabilities at night when out-the-window visibility is limited to lighted objects. The performance of the fusion algorithm is discussed, showing how it effectively removed false alarms from the FLIR and radar data. The fusion process successfully tracked targets of opportunity and classified them accurately according to the incursion hazard they represented.