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.

中文翻译：

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基于变形梯度和图像噪声的矿山变形监测自适应偏移跟踪方法

利用SAR图像强度的偏移跟踪法（OTM）可以检测大变形，弥补了干涉合成孔径雷达（InSAR）技术在大矿山变形监测中的不足，得到了广泛的应用。通过大量的仿真实验发现，OTM的精度与互相关窗口（CCW）中的变形梯度和图像噪声有关，因此应根据变形梯度和噪声水平合理选择CCW尺寸。基于以上结论，本文提出一种基于变形梯度和图像噪声的采矿变形监测自适应逆时针选择方法，该方法考虑变形梯度和图像噪声对变形的影响来选择自适应逆时针。考虑到噪声对偏移跟踪结果的影响，大变形梯度区域选择较小的CCW，小变形梯度区域选择较大的CCW。对于一些特殊区域，会选择特殊的 CCW 进行偏移跟踪。将该方法应用于仿真和实际实验，实验结果表明，该方法具有较高的可靠性和有效性，能够显着提高OTM在采矿变形监测中的精度。