Airspace encounter models, covering close encounter situations that may occur after standard separation assurance has been lost, are a critical component in the safety assessment of aviation procedures and collision avoidance systems. Of particular relevance to unmanned aircraft systems (UAS) is the potential for encountering general aviation aircraft that are flying under visual flight rules (VFR) and which may not be in contact with air traffic control. In response to the need to develop a model of these types of encounters, Lincoln Laboratory undertook an extensive radar data collection and modeling effort involving more than 120 sensors across the U.S. This report describes the structure and content of that encounter model. The model is based on the use of Bayesian networks to represent relationships between dynamic variables and to construct random aircraft trajectories that are statistically similar to those observed in the radar data. The result is a framework from which representative intruder trajectories can be generated and used in fast- time Monte-Carlo simulations to provide accurate estimates of collision risk.
Uncorrelated Encounter Model of the National Airspace System, Version 1.0
2008
113 pages
Report
Keine Angabe
Englisch
Aircraft , Navigation Systems , Aeronautics , Air traffic control systems , Air space , Collision avoidance , Networks , Accuracy , Radar , Monte carlo method , Variables , Unmanned , Safety , Data acquisition , Bayes theorem , Trajectories , Visual flight rules , Intrusion , Collisions , Risk , General aviation aircraft , Simulation , Quick reaction
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