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基于方差分量估计的GB-InSAR三维形变解算方法

白泽朝 王萱 王彦平 余快

华中科技大学学报(自然科学版)2026,Vol.54Issue(3):79-84,6.
华中科技大学学报(自然科学版)2026,Vol.54Issue(3):79-84,6.DOI:10.13245/j.hust.250067

基于方差分量估计的GB-InSAR三维形变解算方法

Research on three-dimensional deformation calculation method of GB-InSAR based on variance component estimation

白泽朝 1王萱 1王彦平 1余快2

作者信息

  • 1. 北方工业大学人工智能与计算机学院,北京 100144
  • 2. 中国空间技术研究院,北京 100094
  • 折叠

摘要

Abstract

The least-squares-based ground-based interferometric synthetic aperture radar(GB-InSAR)method for solving three-dimensional deformation does not account for deformation continuity or measurement error variations between different radar datasets.To address this,the variance component estimation parametric least squares(Para-LSQ-VCE)method was proposed.For one-dimensional line-of-sight deformation observation matrices acquired from radars at different angles,a parameter matrix is constructed to ensure continuous and smooth deformation solutions.Weighted iteration was then applied to precisely allocate weights,thereby enhancing the accuracy of three-dimensional deformation solutions.Experimental results demonstrate that in simulation experiments,the variance component estimation parameterized least squares method achieves up to 91.12%higher accuracy in three-dimensional deformation solutions compared to the least squares method.In field experiments,this method improves three-dimensional deformation solution accuracy by 86.67%.The method proposed in this article has improved the accuracy of GB-InSAR three-dimensional deformation monitoring,which has important theoretical significance and application value for promoting the application of GB-InSAR in the field of precision measurement.

关键词

GB-InSAR/三维形变解算/参数化最小二乘/方差分量估计/雷达

Key words

GB-InSAR/three-dimensional deformation estimation/parameterized least squares/variance component estimation/radar

分类

天文与地球科学

引用本文复制引用

白泽朝,王萱,王彦平,余快..基于方差分量估计的GB-InSAR三维形变解算方法[J].华中科技大学学报(自然科学版),2026,54(3):79-84,6.

基金项目

国家重点研发计划青年科学家项目(2023YFB3905200) (2023YFB3905200)

国家自然科学基金资助项目(42501571) (42501571)

北京市教育委员会科学研究计划项目资助(KM202410009001). (KM202410009001)

华中科技大学学报(自然科学版)

1671-4512

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