The identification of enemy air target's combat intention is an important part of battlefield situation awareness. In order to improve the accuracy of Intention Identification by making full use of the temporal correlation of the detected air target motion state information, an identification of enemy air target's combat intention method is proposed based on Long Short Term Memory(LSTM) network in this paper. Firstly, the simulation platform is utilized to deduce large number of air enemy target data according to four different intentions. Then, the generated data is cleaned and slide window processed to obtain the effective sample set. Finally, the LSTM network is adopted to learn the generated sample set and form the combat intention identification model of enemy air targets. Experimental results show that the prediction accuracy of network can reach 92% by using the LSTM network to learn the time-related characteristic information of data, and the result is better than that of traditional classifier.