The invention relates to the fields of air combat environments, data processing, deep learning and the like, and provides a method for realizing aircraft trajectory prediction by using a long short-term memory (LSTM) network under an uncertain sensing condition. Therefore, the technical scheme adopted by the invention is as follows: the method for predicting the trajectory of the aircraft based on the long-short-term memory network comprises the following steps of: eliminating noise interference carried by a sensor feature vector by using Kalman filtering; data preprocessing including downsampling, invalid value elimination and missing value complementation is carried out on the directly obtained state parameters, in addition, in order to improve the calculation stability, data is subjected to normalization processing, and the value range of input data is included in the interval of [0, 1]; and an LSTM-based trajectory prediction model is created, input and output of the network is defined, and the network is supervised and trained. The invention is mainly applied to the prediction occasion of the flight path of the unmanned aerial vehicle.