This analysis finds improved accuracy in intent recognition of airborne targets using trajectory images, suggesting effective applications in decision-making.
Accurate intent recognition is crucial for decision-makers. The intent behavior of airborne targets is often related to their trajectory movements. Based on this, we construct a trajectory image dataset from the perspective of temporal trajectories and utilize the MobileViT network to achieve trajectory image classification, thereby realizing intent recognition. Experimental results demonstrate that the intent recognition method based on trajectory image classification shows significant advantages in terms of accuracy.
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Du et al. (2025) studied this question.
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