基于密集弧段连接的城市场景时序InSAR方法（EP-InSAR）

郭绍琨; 董杰; 王茹; 廖明生

doi:10.11834/jrs.20265361

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基于密集弧段连接的城市场景时序InSAR方法（EP-InSAR）
EP-InSAR： Exhaustive pair linking strategy for urban ground deformation mapping
2026年30卷第4期页码：916-928
收稿：2025-09-12，

纸质出版：2026-04-07
DOI： 10.11834/jrs.20265361
稿件说明：

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郭绍琨，董杰，王茹，廖明生.2026.基于密集弧段连接的城市场景时序InSAR方法（EP-InSAR）.遥感学报，30（4）： 916-928 DOI： 10.11834/jrs.20265361.

Guo S K，Dong J，Wang R and Liao M S. 2026. EP-InSAR： Exhaustive pair linking strategy for urban ground deformation mapping. National Remote Sensing Bulletin， 30（4）：916-928 DOI： 10.11834/jrs.20265361.

摘要

城市地表及基础设施形变监测对城市安全运行具有重要意义。合成孔径雷达干涉测量技术InSAR（Interferometric Synthetic Aperture Radar）是城市形变监测的重要手段之一。在复杂城市场景中，传统永久散射体InSAR技术PS-InSAR（Permanent Scatter InSAR）易受大气延迟影响、高估相位噪声水平；基于PS弧段的InSAR技术PSP-InSAR（PS Pairs InSAR）通过解算点对参数，可有效提取高质量监测点，但在算力有限时，点对搜索覆盖不足。为此，本文提出一种基于密集弧段连接的时序InSAR方法（Exhaustive Pairs InSAR，EP-InSAR）。该方法首先采用顺次基线连接策略，抑制时空双差相位形变分量，允许仅开展一维弧段参数解算，显著提高计算效率；然后设计双阈值驱动的迭代网络扩张算法，实现对高质量点对的近似穷举，减弱对相位质量幅度先验的依赖，充分发掘稳定监测点；最后，剔除高程与热胀冷缩项获得低频干涉图序列，提取形变时间序列产品。依据上海地区TerraSAR-X（TSX）数据进行实验，结果表明，EP-InSAR方法有效提升了监测点覆盖率，能够筛选出大量不符合传统幅度先验的高质量监测点，其中29.3%监测点的振幅离差指数>0.6；在3000×3000的处理窗口内，提取由6000万条高质量弧段连接的91万监测点，为监测点参数解算提供大量多余观测；最终，发现多处可与卫星历史影像印证的局部形变隐患点。综上，本文提出算法的整体流程已初步实现并行优化，具备工程应用可行性，有望在城市建筑形变普查和健康监测中应用推广。

Abstract

Monitoring urban ground and infrastructure deformation is essential for the safe operation of cities. Interferometric Synthetic Aperture Radar (InSAR) has become a key technology for this purpose. However

in complex urban environments

conventional persistent scatterer InSAR heavily relies on prior constraints

and advanced variants are often limited by high computational demands. These limitations lead to insufficient arc coverage and reduced robustness in time series analysis

especially when deformation is localized and nonlinear.

To address these challenges

we propose exhaustive pairs InSAR (EP-InSAR)

a time series InSAR method that is based on dense arc linking. By sequentially connecting baseline pairs

the linear deformation term is embedded into the phase component of the temporal coherence to reduce the dimensionality of arc parameter estimation. A dual-threshold iterative network expansion strategy is introduced to identify high-quality point pairs in an approximately exhaustive manner

mitigating the reliance on amplitude-based priors. In the implementation

conventional InSAR preprocessing is followed by sequential interferogram formation

1D spectral search for arc parameters

and robust global least-squares adjustment of height residuals and thermal dilation coefficients. Deformation time series are retrieved from a rectified low-frequency interferogram stack

and elevation and thermal components are removed.

Experiments using TerraSAR-X data over Shanghai demonstrate that EP-InSAR increases point coverage

improves arc network connectivity

and reduces global adjustment errors. In a 3000×3000 pixel processing window

the method extracts ~910

000 measurement points connected by ~60

000

000 high-quality arcs

providing substantial redundancy for parameter estimation. Among all the accepted points

29.3% have an amplitude dispersion index larger than 0.6

indicating that many structurally reliable scatterers are discarded under amplitude-based screening alone. The estimated height residual and thermal dilation fields form coherent spatial patterns that match building footprints and material distributions

and the derived time series reveal localized nonlinear deformation that is consistent with construction histories visible in optical satellite imagery.

The EP-InSAR workflow is parallelized and optimized for large-scale processing

showing strong potential for applications in urban structural health monitoring. EP-InSAR provides a practical strategy to approximate exhaustive arc exploration without a prohibitive computational cost

relaxes the dependence on strict amplitude-based screening

and increases sensitivity to local nonlinear deformation under complex scattering conditions. These properties indicate that EP-InSAR can support future large-area urban deformation surveys and routine monitoring of critical infrastructure and building stability.

关键词

Keywords

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