Runway obstacle detection using onboard sensors: Modeling and simulation analysis

In recent years, the increasing demand on the national airspace system (NAS) has propelled further research on new technologies, communication systems, sensors and methods to handle the growing congestion around the terminal area. These include programs such as the runway incursion prevention system (RIPS), automatic dependent surveillance - broadcast (ADS-B), the national aeronautics and space administrationpsilas (NASA) synthetic vision systems (SVS) and more recently, NASApsilas integrated intelligent flight deck (IIFD) project. One of the aspects of the IIFD is an external hazard monitor (EHM) function that interfaces with onboard terrain and obstacle databases, communications, and also with aircraft sensors. The EHM is envisioned to provide improved obstacle detection and hazard evaluation with added integrity and reliability. The work in this paper is performed in support of the EHM function and presents a modeling and simulation framework that models the aircraft sensors, synthesizes their measurements and analyzes their runway obstacle detection capability using both simulations and flight data playback. Various sensor parameters, measurement errors and physical properties of potential runway hazards/objects are evaluated in the simulations. Particular sensors that are considered for this work are: airborne laser scanner (ALS), 3D imaging camera, and forward-looking infrared camera (FLIR). The sensors are evaluated with regard to detection metrics such as probability of detection and time-to-alarm. Furthermore, results from the simulations using playback of actual flight test data in the vicinity of Braxton county airport (K48I), WV and Reno (RNO), NV are presented.