Three-dimensional trajectory is a complex time series with continuity and interaction.Aiming at the problem of UAV flight trajectory prediction and by using the deep learning theory,a method for UAV flight trajectory prediction based on bidirectional Gated Recurrent Unit (GRU) is proposed,which can further improve the utilization rate of trajectory information.Firstly,the UAV flight dynamics model is established,and the flight trajectory samples in different states are obtained by simulation.Secondly,the Mean Square Error (MSE) is used as the loss function to determine the parameters of hidden nodes and iterations of the bidirectional GRU model.Finally,the Adamax algorithm is used to optimize the bidirectional GRU model for realizing the prediction of the UAV flight trajectory.Experimental results show that:1) The Mean Absolute Errors(MAE)of the prediction results of the bidirectional GRU model in the X,Y,and Z axis directions are all within 5.0 m,and the average time for trajectory prediction is 4.2 ms approximately;and 2) Compared with RNN and GRU models,our method has better prediction effect.Thus it will have fine application value.