Analysis of air traffic track data with the autobayes synthesis system

  • Authors:
  • Johann Schumann;Karen Cate;Alan Lee

  • Affiliations:
  • SGT, Inc./ NASA Ames, Moffett Field, CA;NASA Ames, Moffett Field, CA;NASA Ames, Moffett Field, CA

  • Venue:
  • LOPSTR'10 Proceedings of the 20th international conference on Logic-based program synthesis and transformation
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controller. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and detection of continuous descent approaches (CDA) can be supported by code generated from compact AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.