Research on the improved LSTM for target trajectory prediction

With the rapid development of modern traffic network, it is very important to accurately predict the trajectory of key traffic nodes. Aircraft navigation path, as a kind of data with complex temporal characteristics, is often affected by climate change and environmental disturbance, which makes the dynamic prediction of path characteristics a challenge. In this context, a novel trajectory prediction technique combining LSTM model is introduced in this study. The technique achieves accurate prediction of the target path through deep training of a large amount of data. The experimental results fully demonstrate the significant advantages of this method compared with traditional algorithms in the accuracy of flight target prediction and data processing efficiency.