Flight Trajectory Prediction Based on Residual Neural Network and LSTM
FANG Wei
TANG Miao
YAN Wenjun
ZHANG Tingting
Abstract：Aiming at the problem of insufficient accuracy and large error in flight trajectory prediction,a flight trajectory pre-diction algorithm combining residual neural network and LSTM is proposed.Firstly,the longitude,latitude and altitude data are converted into the position coordinates of the aircraft in the ground coordinate system by coordinate conversion,and then the coordi-nate data are normalized.Secondly,the residual neural network is used to read the sequence and automatically learn the internal characteristics.Finally,the LSTM is used to process the time series information of the data.The experimental results show that com-pared with LSTM and CNN+LSTM models,the loss function,root mean square error and average absolute error of this model are smaller,and the effect is better.The predicted trajectory can reflect the track changes of the real trajectory.
Keywords：trajectory predictiontime seriesresidual neural networklong short-term memory network
Publication Date：2023-10-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 42-46 )