Research on Target Value Assessment Method Based on Attention Mechanism

Under the condition of informatized joint combat system, the traditional target value analysis method based on human judgment is no longer able to quickly and accurately judge the target value from the massive battlefield information. In this paper, combining with the attention mechanism model, we propose a dual-driven target value assessment framework based on target and data, and construct data-driven and purpose-driven attention mechanism models respectively. By selecting multiple features and calculating the saliency of cue targets, the results of the two models are fused to screen out the noticed cue targets and further expanded to form a high-value target set. The experimental results show that the proposed target value assessment model based on attention mechanism is effective, and the matching rate between the actual strike targets and the high-value targets obtained by the model reaches 92%, which is in line with the actual situation of combat and can reflect the cognitive process of the commander to some extent.