• The Advanced Trajectory Modeling project demonstrated that aircraft-derived data can be successfully used by TBFM and ERAM to predict more accurate trajectories for PBN arrivals for both constrained and unconstrained descents. • The aircraft-derived data investigated provided limited accuracy gains when constructing a GIM-S advisory. The GIM-S advisory could not obtain a top of descent or trajectory, speed and profile data from the aircraft, as the aircraft is not aware of the speed being considered until a clearance is delivered. • Several factors drive the uncertainty in prediction. These include: forecast wind; errors in aircraft performance models; thrust modeling; and modeling of deceleration segments. • Further research to mitigate these uncertainties can further improve ground automation models.
Advanced trajectory modeling: Use of aircraft-derived data in ground automation
01.04.2018
2022281 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Aircraft trajectory prediction for terminal automation
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