An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

The monitoring of large-gradient deformation caused by coal mining is of great significance to the prevention and management of disasters in mining areas. The interferometric synthetic aperture radar (InSAR) method captures the small-gradient ground deformation on the edge of the subsidence basin accurately but is unreliable for capturing large-gradient deformation. The intensity-based pixel-tracking method (e.g., the normalized cross-correlation (NCC) method) can overcome the limitations of InSAR's maximum detectable displacement gradient and incoherence. However, the pixel-tracking method is sensitive to template size. It is difficult to estimate ground subsidence accurately by the conventional pixel-tracking method with fixed template size. In this paper, the signal-to-noise ratio (SNR) is redefined and an improved locally adaptive template size method is proposed by identifying optimal template adaptively based onmaximization of the redefined SNR. The constraint radius is used to constrain the search area in this improved method. The frequency of misrepresentation is reduced by finding the peak of the correlation coefficient surface within the search area. Both simulation data and real ground subsidence data are used to test this algorithm. The results show that this method can improve monitoring accuracy compared with the traditional pixel-tracking method for fixed template size.