Recognition and prediction of group target intention in multi-domain operations

There are many challenges in multi-domain operations, such as multiple entities, changeable formations and diverse intentions, which make it difficult to comprehensively utilize multiple knowledge. Therefore, manual judgment is mainly used, resulting in a low level of automation. In order to realize the automatic deduction of the situation by the computer, two difficult problems need to be solved: the graphical modeling of knowledge and the synthesis of intention reasoning. Based on the knowledge map of airspace management and control, a multi-domain operational tactical rule base, the mapping relationship between formation and scene situation is built. A multi-entity hierarchical Bayesian network-based group target intent recognition and prediction method is proposed. Firstly, the state and event information of the target entity in the group is used to construct the behavioral reasoning layer of the target combat entity. Secondly, based on the temporal rules, relative distance and heading information of combat entities, a reasoning layer of similar target element intention is constructed. Finally, the general intention reasoning layer of group targets under multi-domain operations is constructed by using the entity sequence collaboration relationship and formation information. Taking the simulation data of aircraft carrier group activities as an example, it is verified that the algorithm proposed in this paper can obtain relatively reliable intention inference results. © 2022 Chinese Institute of Electronics. All rights reserved.