地表大梯度时序形变的确定方法、装置、设备及介质

By screening super master images for registration and grouping thresholds, and combining robust estimation, the problems of pixel target mismatch and gross errors in SAR pixel offset tracking technology are solved, and high-precision monitoring of large gradient temporal deformation of the ground surface is realized.

CN122151083BActive Publication Date: 2026-07-17NORTHEASTERN UNIV CHINA

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NORTHEASTERN UNIV CHINA
Filing Date
2026-05-07
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing SAR pixel offset tracking technology is prone to pixel mismatch and gross errors in large gradient deformation monitoring, resulting in large errors in time series calculation results and affecting the accuracy of surface deformation monitoring.

Method used

By screening super master images for registration, SLC images are divided into subsets based on grouping thresholds, robust estimation is used to reduce the impact of gross errors, short-time series deformation is determined, and finally, the large-gradient temporal deformation of the land surface is obtained by connecting them.

Benefits of technology

It improves the monitoring accuracy of large-gradient temporal deformation of the Earth's surface, solves the mismatch problem caused by significant changes in pixel position, and reduces the impact of gross errors on the results.

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Abstract

本申请公开了一种地表大梯度时序形变的确定方法、装置、设备及介质,涉及数据处理领域。将SAR卫星影像处理为SLC影像,并从所有SLC影像中筛选出一个超级主影像;基于超级主影像,对所有SLC影像进行配准;基于所有配准后的SLC影像,确定所有SLC影像的分组阈值;基于分组阈值,对所有配准后的SLC影像进行分组,得到SLC影像子集;确定SLC影像子集的短时间序列形变;基于SLC影像子集的短时间序列形变,利用抗差估计确定相邻的SLC影像子集中的主影像的最终偏移量;基于所有相邻的SLC影像子集中的主影像的最终偏移量,将所有SLC影像子集的短时间序列偏移量进行连接,得到地表大梯度时序形变。
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