Latest revision as of 19:58, 3 February 2021

Abstract

on Techniques for Capturing and Comparing Trajectory Predictor Capabilities and Requirements Robert A. Vivona L-3 Communications, Billerica, MA 01821 Karen T. Cate and Steven M. Green NASA Ames Research Center, Moffett Field, CA 94035 Recent research has increased focus on the conceptual design, development and use of airand ground-based aircraft trajectory prediction capabilities to support advanced Air Traffic Management concepts. In both the United States and Europe, the sharing of fourdimensional trajectory information between many automation systems will be necessary for successful operations. Understanding the functional and performance differences between disparate trajectory predictors is critical for enabling this system interoperability. Documented capabilities for four existing trajectory predictors were compared to identify commonalities and differences. For effective comparison, it was first necessary to abstract the prediction capabilities of each trajectory predictor. Three abstraction techniques were developed. The first separated the description of modeled aircraft behavior from the associated mathematical models used to integrate the predicted trajectory. The second defined a conceptual boundary between the trajectory predictor and its client application. The third eliminated the use of domain specific terminology. The abstraction techniques proved not only beneficial for comparing trajectory prediction capabilities, but also for defining trade-offs between the compatibility and accuracy of disparate TPs to achieve system interoperability.

Original document

The different versions of the original document can be found in:

• http://www.aviationsystemsdivision.arc.nasa.gov/publications/more/other/AF2008098.pdf

• http://arc.aiaa.org/doi/pdf/10.2514/6.2008-7408,

http://dx.doi.org/10.2514/6.2008-7408

• https://www.aviationsystemsdivision.arc.nasa.gov/publications/more/other/AF2008098.pdf,

https://arc.aiaa.org/doi/10.2514/6.2008-7408,

https://academic.microsoft.com/#/detail/2331539062