Improved multi-aircraft ground trajectory prediction through wind forecast error
filtering
John Lygeros
(ETH Automatic Control Laboratory - Zurich)
Accurate trajectory prediction plays a fundamental role in advanced air traffic
control operations, because it forms the basis for (among others) conflict detection and
resolution schemes. We discuss how the radar measurements of multiple aircraft flying in
a region of the airspace can be used to extract information about meteorological wind
forecast errors, hence improving the accuracy of ground based aircraft trajectory
prediction. We show how this problem be formulated as a high dimensional state estimation
problem and develop a novel particle filtering algorithm that exploits the special
structure of the problem to solve it in realistic scale situations. The effectiveness of
the novel algorithm is demonstrated on feasibility studies involving multiple aircraft
(from one to several hundred). The studies show that in the presence of multiple aircraft
the trajectory prediction results approach the theoretical limit of accuracy under these
conditions.
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