4.7 Article

An Adaptive Offset-Tracking Method Based on Deformation Gradients and Image Noises for Mining Deformation Monitoring

期刊

REMOTE SENSING
卷 13, 期 15, 页码 -

出版社

MDPI
DOI: 10.3390/rs13152958

关键词

adaptive cross-correlation window; offset-tracking; deformation gradients; mining deformation monitoring

资金

  1. National Key Research and Development Program of China [2017YFE0107100]
  2. National Natural Science Foundation of China [51774270, 41604005]
  3. Water Resources Science and Technology Project of Jiangsu Province

向作者/读者索取更多资源

The study proposes an adaptive CCW selection method based on deformation gradients and image noises to improve the accuracy of the offset-tracking method in mining deformation monitoring.
The offset-tracking method (OTM) utilizing SAR image intensity can detect large deformations, which makes up for the inability of interferometric synthetic aperture radar (InSAR) technology in large mining deformation monitoring, and has been widely used. Through lots of simulation experiments, it was found that the accuracy of OTM is associated with deformation gradients and image noises in the cross-correlation window (CCW), so CCW sizes should be selected reasonably according to deformation gradients and noise levels. Based on the above conclusions, this paper proposes an adaptive CCW selection method based on deformation gradients and image noises for mining deformation monitoring, and this method considers influences of deformation gradients and image noises on deformations to select adaptive CCWs. In consideration of noise influences on offset-tracking results, smaller CCWs are selected for large deformation gradient areas, and larger CCWs are selected for small deformation gradient areas. For some special areas, special CCWs are selected for offset-tracking. The proposed method is implemented to simulation and real experiments, and the experiment results demonstrate that the proposed method with high reliability and effectiveness can significantly improve the accuracy of OTM in mining deformation monitoring.

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