文献类型：期刊文献

英文题名：An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

作者：Huang, Jilei[1,2];Deng, Kazhong[2];Fan, Hongdong[2,3];Lei, Shaogang[2];Yan, Shiyong[2];Wang, Lei[2]

第一作者：Huang, Jilei

通讯作者：Deng, KZ[1]

机构：[1]Henan Univ Econ & Law, Coll Resources & Environm, Zhengzhou, Henan, Peoples R China;[2]China Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou, Peoples R China;[3]Chengdu Univ Technol CDUT, State Key Lab Geohazard Prevent & Geoenvironm Pro, 1 Third East Rd Erxian Qiao, Chengdu, Sichuan, Peoples R China

第一机构：河南财经政法大学资源与环境学院

通讯机构：[1]corresponding author), China Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou, Peoples R China.

年份：2017

卷号：2017

外文期刊名：JOURNAL OF SENSORS

收录：;EI(收录号：20174104260704);Scopus(收录号：2-s2.0-85030785001);WOS:【SCI-EXPANDED(收录号:WOS:000411984800001)】；

基金：This work was supported by the National Natural Science Foundation of China (no. U1361214 and no. 41604005), National Key Research and Development Program (no. 2016YFC0501107), Natural Science Foundation of Jiangsu Province (no. BK20150189), and the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology) (no. SKLGP2016 K008).

语种：英文

外文关键词：Coal industry - Cutting machines (mining) - Deformation - Disaster prevention - Pixels - Subsidence - Synthetic aperture radar

摘要：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.