Volume 13 Issue 1
Feb.  2024
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XIE Xin, DENG Yunkai, YANG Zhijun, et al. Topography-assisted UAV InSAR image registration method with image partition[J]. Journal of Radars, 2024, 13(1): 116–133. doi: 10.12000/JR23182
Citation: XIE Xin, DENG Yunkai, YANG Zhijun, et al. Topography-assisted UAV InSAR image registration method with image partition[J]. Journal of Radars, 2024, 13(1): 116–133. doi: 10.12000/JR23182

Topography-assisted UAV InSAR Image Registration Method with Image Partition

DOI: 10.12000/JR23182
Funds:  The National Key Research and Development Project (2021YFC3001903), The National Natural Science Foundation of China (62101036, 61971037), Beijing Institute of Technology Research Fund Program for Young Scholars
More Information
  • Corresponding author: DENG Yunkai, yunkai_bit@bit.edu.cn
  • Received Date: 2023-10-04
  • Rev Recd Date: 2024-01-02
  • Available Online: 2024-01-04
  • Publish Date: 2024-01-11
  • Miniaturized and lightweight Unmanned Aerial Vehicles (UAV) provide a flexible platform for Synthetic Aperture Radar (SAR). The application of UAV Interferometric SAR (InSAR) is gradually increasing in interferometric measurement fields. UAVs are small and light, which are easily affected by airflow disturbances. Their trajectories are nonlinear and unparallel when adopting the multipass mode for interferometry. The nonlinear and unparallel trajectories result in geometric distortion between the interferometric image pairs. Under complex topography conditions, the interferometric image pairs of UAVs have large offsets that are obviously space-dependent, thereby resulting in substantial technical challenges during image registration. Conventional image registration methods based on polynomial fitting are no longer applicable. In this study, we proposed an image registration method based on image partition with topography assistance. First, an elevation threshold is generated based on the UAV trajectories, and the measurement area is partitioned using the assisted topography. Then, a polynomial fitting model is constructed for offsets within each partition with constraints applied at the partition boundaries for joint optimization. Finally, continuous global offset fitting surfaces are obtained, and precise image registration is achieved by resampling the slave image. The effectiveness of the proposed method is preliminarily validated using real measurement data obtained from UAV InSAR in the P-band.

     

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