Journal of System Simulation ›› 2026, Vol. 38 ›› Issue (2): 346-359.doi: 10.16182/j.issn1004731x.joss.24-1159

• Machine Learning Algorithms • Previous Articles    

Research on UAV Target Tracking Algorithm for Simulation Scenarios

Li Xinyi, Wang Zhenfei, Wu Han   

  1. School of Computer Science and Artificial Intelligence, Zhengzhou University, Zhengzhou 450000, China
  • Received:2024-10-19 Revised:2024-12-30 Online:2026-02-18 Published:2026-02-11
  • Contact: Wu Han

Abstract:

To address the need for automatic UAV tracking of moving targets in simulated experiments, this paper proposed a long-term automatic tracking method based on an improved channel and spatial reliability-aware tracker (CSRT) algorithm. The target edge features were detected using the Laplacian of guided filter (LOGF) through guided filtering and then fused with the histogram of oriented gradient (HOG) and color names (CN) features to enhance the algorithm's discriminative ability for the target. To evaluate the target state, the paper used average peak correlation energy and perceptual hash Hamming distance. When the target was occluded, the paper employed YOLOv8 for target localization and fed the localization results back into the tracking algorithm to continue tracking. Simulation results demonstrate that the algorithm can maintain long-term stable tracking of the target even when the target is occluded in the constructed simulation environment, providing a favorable simulation experimental environment for the research on UAV target tracking algorithms.

Key words: channel and spatial reliability-aware tracker(CSRT), edge feature, target positioning, YOLOv8, virtual target dataset

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