Airspace Encounter Models

There is a newer version of the record available.

Published October 1, 2021 | Version v2.0.0
Software Open

Airspace-Encounter-Models/em-model-manned-bayes: October 2021

Authors/Creators

  • 1. @mit-ll
  • 2. @sisl

Contributors

Researcher:

  • 1. @mit-ll

Description

The Bayesian network encounter models are a collection of MATLAB scripts that produce random samples from models of how different aircraft behave, as previously documented in MIT Lincoln Laboratory technical reports. All these models were originally developed by MIT Lincoln Laboratory. Majority of these samples are of one independent aircraft track and a single sample is insufficient for a complete synthetic encounter. 

Each manned aircraft model is a Bayesian Network, a representation of a multivariate probability distribution as a directed acyclic graph. Models are trained using aircraft operational data derived from radar or other sensing system flight track data.

Files

Airspace-Encounter-Models/em-model-manned-bayes-v2.0.0.zip

Files (10.8 MB)

Additional details

Related works

Is supplement to
https://github.com/Airspace-Encounter-Models/em-model-manned-bayes/tree/v2.0.0 (URL)