In order to assist commanders in making decisions efficiently， this paper makes researches on the grouping of operational targets in situation awareness. Aiming at the characteristics of numerous targets， different functions and complex interrelationships in the operational system of systems， the graph matching idea is used to solve the target group type identification problem. A graph-based target group representation method is proposed， where the target is abstracted as a node and the interrelation is abstracted as an edge， which depicts the targets and their mutual relationship. A graph matching network model is designed to identify the type of target group. The model can jointly learn the vector representation of the group to be identified and the group of known types. The type of target group can be identified by calculating the similarity between the two groups. Experimental results show that the proposed method can efficiently identify the type of target groups.

The situation data in complex battlefield environment presents large-scale and fragmented features， the knowledge graph technology is applied to situation awareness to recognize operations from the perspective of integrity and relevance. The knowledge graph of operational action is constructed. The situation data such as operational action types， operational forces and attributes are organized in the form of graph to realize the correlation of operational knowledge. An operational action recognition model based on knowledge is designed. The model can fully utilize the attribute information and association information in the graph to enrich the vector representation of entities. By measuring the authenticity of triples， the operational action types and the relationships between combat forces can be recognized. Experimental results show that the proposed method can effectively recognize operations and help the commander to analyze the battlefield situation in depth.