Tactical intention recognition provides decision support for commanders to understand the battlefield posture and develop the plan operations.How to structure intention recognition is a challenging problem in situation analysis.Aiming at the integration and transmission of battlefield situational uncertainty in traditional tactical intent recognition methods and the solidification of inference templates,a target tactical intent inference framework is constructed based on the acquisition of dynamic operational knowledge of the target for explaining the operational elements in the course of enemy combat operations.Based on the characteristics of combat plan,a target tactical intention recognition method based on operational knowledge neural network (OKNN) is proposed. OKNN takes the air target group as the unit and enhances the flexibility of model reasoning by dynamically building a set of entity fragments based on operational knowledge in real time.The model is based on an empirical training sample plan library,which can dynamically and adaptively adjust the spatial distribution of target tactical intent results,greatly eliminating the integration and transmission of uncertainty.The simulation results indicate that the reasoning model is feasible and effective.