Improved DIMP Tracking Method for Terminal Guidance Applications

We propose an enhanced algorithm for the DIMP target tracking system, addressing its limitations in feature capability and its vulnerability to interference from similar targets in terminal guidance scenarios. The spatial and color feature weights of the target are enhanced by introducing CBAM attention mechanism in the feature extraction stage. The fusion module processes the extracted multi-stage feature map to acquire enhanced positional and semantic information. After the mutual correlation generates the target confidence, adaptive Kalman filtering is used for trajectory prediction and classification, and accurate target tracking is finally realized. EXPERIMENTAL DEMONSTRATION: The experimental findings indicate that the algorithm enhances both the success rate and accuracy by approximately 3%-4% on the Guidance-UAV and UAV123 datasets and improves the EAO metric of VOT2018 by 1.81%. It demonstrates good, generalized tracking capability and advantages of terminal guidance application, and can meet the relevant requirements.