Aircraft Trajectory Prediction With Enriched Intent Using Encoder-Decoder Architecture

Aircraft trajectory prediction is a challenging problem in air traffic control, especially for conflict detection. Traditional trajectory predictors require a variety of inputs such as flight-plans, aircraft performance models, meteorological forecasts, etc. Many of these data are subjected to envir...

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Veröffentlicht in:	IEEE access Jg. 10; S. 17881 - 17896
Hauptverfasser:	Tran, Phu N., Nguyen, Hoang Q. V., Pham, Duc-Thinh, Alam, Sameer
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	4D trajectory Air traffic control Aircraft Aircraft detection Aircraft performance Aircraft trajectory prediction Atmospheric modeling Atmospheric models Coders Collision avoidance convolution neural network encoder-decoder Encoders-Decoders Error reduction Flight plans machine learning Performance enhancement Prediction models Predictive models recurrent neural network Recurrent neural networks Root-mean-square errors Traffic conflicts Traffic models Trajectories Trajectory Uncertainty Weather forecasting
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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