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<p>Tracking a fixed-wing unmanned aerial vehicle (UAV) plays a key role in the aerospace applications, but this research area lacks a high-diversity and large-scale benchmark dataset, which is a key factor for both the comprehensive evaluation of UAV to UAV (UAV2UAV) tracking algorithms and the development of deep learning methods. It is thus essential to construct a UAV2UAV dataset to fill the gap and advance the research in this domain. To this end, we release here a large-scale dataset, UAV2UAV-2 dataset, for a fixed-wing UAV tracking. Our UAV2UAV-2 dataset includes 49 videos with more than 27k frames in total. A training dataset with more than 4k images and various background scenarios is also provided, which can be used to further validate the training process. A comprehensive performance evaluation of 24 tracking methods is carried out on this dataset. Three representative tracking methods which are trained on the training dataset achieve superior results compared to the original corresponding methods. This indicates that training with dedicated data can improve tracking performance, and this approach can be extended to more tracking algorithms. A detailed analysis of the performance results is also provided. The data will be available at: <a href="https://github.com/zxysysu/UAV2UAV-2">https://github.com/zxysysu/UAV2UAV-2</a>.</p>

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Tracking a fixed-wing unmanned aerial vehicle: an experimental evaluation

  • 期刊论文

  • 发表日期：

    2026年2月24日

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  • Yong Wang,
  • Xiangyu Zhu,
  • Zhiyang Sun,
  • Robert Laganiere,
  • Lu Ding

摘要

Tracking a fixed-wing unmanned aerial vehicle (UAV) plays a key role in the aerospace applications, but this research area lacks a high-diversity and large-scale benchmark dataset, which is a key factor for both the comprehensive evaluation of UAV to UAV (UAV2UAV) tracking algorithms and the development of deep learning methods. It is thus essential to construct a UAV2UAV dataset to fill the gap and advance the research in this domain. To this end, we release here a large-scale dataset, UAV2UAV-2 dataset, for a fixed-wing UAV tracking. Our UAV2UAV-2 dataset includes 49 videos with more than 27k frames in total. A training dataset with more than 4k images and various background scenarios is also provided, which can be used to further validate the training process. A comprehensive performance evaluation of 24 tracking methods is carried out on this dataset. Three representative tracking methods which are trained on the training dataset achieve superior results compared to the original corresponding methods. This indicates that training with dedicated data can improve tracking performance, and this approach can be extended to more tracking algorithms. A detailed analysis of the performance results is also provided. The data will be available at: https://github.com/zxysysu/UAV2UAV-2.