The target state data in the process of air combat confrontation presents the characteristics of time sequence and multi-dimensionality.In order to further improve the accuracy of target intention recognition, an LSTM target recognition method based on improved attention mechanism is proposed, and the target intention recognition that may occur in air combat is treated as a multi-classification problem.Firstly, the feature sequence is generated by the real-time state data of the target.Then, the attention mechanism is used to improve the feature learning ability of the target, enhance the state feature representation of the main target in the air combat process, and obtain the feature vector with weight allocation.Finally, the LSTM network is used to train the target feature vector, and the target intention is recognized through the softmax layer.The simulation results show that the proposed method effectively enhances the feature learning to the target by using the attention mechanism, and further improves the recognition accuracy of the LSTM network, which is scientific and effective.