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.
Original language | English |
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Number of pages | 34 |
Publication status | Published - 2017 |
Event | 12th USA/Europe Air Traffic Management Research and Development Seminar - Seattle, United States Duration: 26 Jun 2017 → 30 Jun 2017 Conference number: 12 http://www.atmseminarus.org/12th-seminar/papers/ |
Conference
Conference | 12th USA/Europe Air Traffic Management Research and Development Seminar |
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Abbreviated title | ATM 2017 |
Country/Territory | United States |
City | Seattle |
Period | 26/06/17 → 30/06/17 |
Internet address |
Keywords
- ADS-B
- Aircraft performance
- Data mining
- Maximum likelihood estimation