Print Email Facebook Twitter Modeling aircraft performance parameters with open ADS-B data Title Modeling aircraft performance parameters with open ADS-B data Author Sun, Junzi (TU Delft Control & Simulation) Ellerbroek, Joost (TU Delft Control & Simulation) Hoekstra, J.M. (TU Delft Control & Simulation) Date 2017 Abstract Open access to flight data from ADS-B (Automatic Dependent Surveillance Broadcast) has provided researchers more insights for air traffic management than aircraft tracking alone. With large quantities of trajectory data collected from a wide range of different aircraft types, it is possible to extract accurate aircraft performance parameters. In this paper, a set of more than thirty parameters from seven distinct flight phases are extracted for common commercial aircraft types. It uses various data mining methods, as well as a maximum likelihood estimation approach to generate parametric models for these performance parameters. All parametric models combined can be used to describe a complete flight that includes takeoff, initial climb, climb, cruise, descent, final approach, and landing. Both analytical results and summaries are shown. When available, optimal parameters from these models are also compared with the Base of Aircraft Data and Eurocontrol aircraft performance database. This research not only presents a comprehensive set of methods for extracting different aircraft performance parameters but also provides a first part of open-source parametric performance models that is ready to be used by the ATM community. Subject ADS-BAircraft performanceData miningMaximum likelihood estimation To reference this document use: http://resolver.tudelft.nl/uuid:7dc6ecdc-28f4-4d07-a08b-494be45d6fb6 Source 12th Seminar Papers: 12th USA/Europe Air Traffic Management Research and Development Seminar Event 12th USA/Europe Air Traffic Management Research and Development Seminar, 2017-06-26 → 2017-06-30, Seattle, United States Part of collection Institutional Repository Document type conference paper Rights © 2017 Junzi Sun, Joost Ellerbroek, J.M. Hoekstra Files PDF 12th_ATM_RD_Seminar_paper_66.pdf 1.05 MB Close viewer /islandora/object/uuid:7dc6ecdc-28f4-4d07-a08b-494be45d6fb6/datastream/OBJ/view