Impact of sensors on collision risk prediction for non-cooperative traffic in terminal airspace

• Main Authors: Wang, John Chung-Hung, Tan, Shi Kun, Koay, Lynette Jie Ting, Low, Kin Huat
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Aeronautical engineering::Aviation; Aircraft; Sensors
• Online Access: https://hdl.handle.net/10356/144322
• Institution: Nanyang Technological University

The availability of off the shelf, easy to control, unmanned aerial systems (UAS) on the market has led to an increase in report of UAS incursion into terminal airspace. Such incursions often lead to airport shutdowns due to safety concern and could cause a cascading disruption to airline operations throughout the region. A better assessment tool for the collision risk between the existing air traffic and the intruder could help reduce unnecessary disruption to air traffic operations. Work has been done on the assessment of such risk using probabilistic UAS positions prediction based on Monte-Carlo simulations, under the assumption of a non-cooperative intruder with worst-case intention aiming at the flight corridor. Alert areas around the runway and the aircraft flight path could be constructed using the collision prediction method, albeit only valid under specific conditions. The accuracy of the predictions could be further improved with the incorporation of ground-based tracking equipment. This paper looks into how the availability of UAS tracking information could be used to complement the collision prediction algorithm, and how its inclusion affects the collision risk assessment.