Tactical Intention Recognition Method of Air Combat Target Based on BiLSTM network

Abstract

As an important support for modern air combat intelligent auxiliary decision-making, real-time and high-precision target intent recognition addresses the foundation for realizing deep situational awareness and creating tactical opportunities. Aiming at the limitation of the existing algorithms such as dependence on empirical knowledge, difficulty in extracting the full temporal characteristics, and inability to meet the requirements of actual air combat, this paper proposes a target tactical intention recognition algorithm based on bi-directional Long Short-Term Memory (BiLSTM). Firstly, we analyze the air combat mechanism to construct the target tactical intention space based on the tactical layer. Specifically, suitable characteristics are selected to describe the intention space. We then design a recognition method considering the characteristic of the tactical intention space. Finally, compared with other algorithms, the simulation results show the effectiveness of the proposed method, which outperforms other methods in terms of accuracy at 92%. And the results are more practical.