Bayesian Inference of Aircraft Initial Mass

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientific

8 Citations (Scopus)
111 Downloads (Pure)

Abstract

Aircraft mass is a crucial piece of information for studies on aircraft performance, trajectory prediction, and many other ATM topics. However, it is a common challenge for researchers who have no access to this proprietary information. Previously, several studies have proposed methods to estimates aircraft weight, most of which are focused on specific parts of the flight. Often due to inaccurate input data or biased assumptions, a significant number of estimates can result outside of the weight limitation boundaries. This paper proposes an approach that makes use of multiple observations to get a better estimate for a complete flight. By looking at flight data from a complete trajectory and calculating aircraft mass at different flight phases based on different methods, together with fuel flow models, multiple observations of aircraft initial mass can then be derived. Using the Bayesian inference method, final estimates can be made with a higher level of confidence.
Original languageEnglish
Title of host publication12th Seminar Papers
Subtitle of host publication12th USA/Europe Air Traffic Management Research and Development Seminar
Number of pages9
Publication statusPublished - 2017
Event12th USA/Europe Air Traffic Management Research and Development Seminar - Seattle, United States
Duration: 26 Jun 201730 Jun 2017
Conference number: 12
http://www.atmseminarus.org/12th-seminar/papers/

Conference

Conference12th USA/Europe Air Traffic Management Research and Development Seminar
Abbreviated titleATM 2017
CountryUnited States
CitySeattle
Period26/06/1730/06/17
Internet address

Keywords

  • aircraft mass
  • weight estimation
  • Bayesian inference

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