The University of Southampton
University of Southampton Institutional Repository

Modelling the dispersion of aircraft trajectories using Gaussian processes

Eerland, Willem, Box, Simon and Sobester, Andras (2016) Modelling the dispersion of aircraft trajectories using Gaussian processes Journal of Guidance, Control, and Dynamics, pp. 1-28. (doi:10.2514/1.G000537).

Record type: Article


This work investigates the application of Gaussian processes to capturing the probability distribution of a set of aircraft trajectories from historical measurement data. To achieve this, all data are assumed to be generated from a probabilistic model that takes the shape of a Gaussian process.

The approach to Gaussian process modelling used here is based on a linear expansion of trajectory data into set of basis functions that may be parametrized by a multivariate Gaussian distribution. The parameters are learned through maximum likelihood estimation.

The resulting probabilistic model can be used for both modelling the dispersion of trajectories along the common flightpath and for generating new samples that are similar to the historical data.

The performance of this approach is evaluated using three trajectory datasets; toy trajectories generated from a Gaussian distribution, sounding rocket trajectories that are generated by a stochastic rocket flight simulator and aircraft trajectories on a given departure path from DFW airport, as measured by ground-based radar. The results indicate that the maximum deviation between the probabilistic model and test data obtained for the three data sets are respectively 4.9%, 7.6% and 13.1%.

PDF paper_jgcd_preprint.pdf - Accepted Manuscript
Download (4MB)
PDF paper.pdf - Other
Download (4MB)

More information

Submitted date: 21 March 2016
Accepted/In Press date: 17 June 2016
e-pub ahead of print date: 25 August 2016
Organisations: Computational Engineering & Design Group, Transportation Group


Local EPrints ID: 399818
ISSN: 0731-5090
PURE UUID: ac60fd77-b295-4461-abf9-42595acfa862
ORCID for Willem Eerland: ORCID iD
ORCID for Andras Sobester: ORCID iD

Catalogue record

Date deposited: 30 Aug 2016 09:23
Last modified: 17 Jul 2017 18:19

Export record


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.