关键词: 群组态势识别, 门控循环神经网络, 注意力机制

Abstract: In the modern air battlefield, the results of the intentional determination of the enemy air operations group directly affect our mastery of the situation and the decision-making. Therefore, the assessment of the air group situation is an important task of the modern battlefield. The air combat groups usually perform the corresponding intent according to the mission, monitor the relevant process and mine the corresponding features from the acquired data, and then learn and predict through the intelligent method. This paper proposes a recognition method based on GRU-Attention neural network, which inputs the pre-processed behavior event library into the GRU neural network  to mine deep features. The corresponding weight assignment is automatically calculated by Attention mechanism. Finally, the input information is classified by the softmax layer. The experimental results show that the accuracy of the GRU-Attention situation identification method reaches 96.10%, which verifies the accuracy, efficiency and stability of the proposed method. The proposed method has important theoretical and practical significance for enriching the neural network identification method system and improving the assessment accuracy of the air group configuration potential.

Key words: group situation recognition, Gated Recurrent Unit neural network, attention mechanism