Deformation monitoring and risk identification of sea-crossing bridges are essential to mitigate hazards and prevent loss of human life and property. Satellite-based Synthetic Aperture Radar Interferometry (InSAR) technology can detect millimeter-scale deformation, showing unique advantages in the safety monitoring of sea-crossing bridges. However, the existing InSAR methods only extract point-like targets (PTs) based on the coherent index, but ignores the analysis of multiple SAR incoherent information and the foreground-background scattering characteristics differences of bridges, leading to low-density and low-accuracy of PTs on sea-crossing bridges. Moreover, most InSAR-based studies identified structural risks according to deformation measurements without fully considering the various safe deformation ranges of different structural components, resulting in high false-alarm/miss-detection rates in structural risk identification of sea-crossing bridges. To address these issues, a structure knowledge-InSAR integration approach is developed for high-precision deformation monitoring and reliable risk identification of sea-crossing bridges. Firstly, the SAR incoherent information and foreground-background scattering characteristics of the bridge structure are analyzed and applied to improve the density of extractable PTs and remove the incorrect noise signals. Then, the bridge structural mechanics model is combined with the InSAR time-series displacements to analyze the mechanical property degradation of different bridge components, improving the reliability of InSAR-based structural risk identification. This approach is applied to the Stonecutters Bridge and Tsing Ma Bridge using the TerraSAR-X and COSMO-SkyMed images from 2011 to 2012 and the Sentinel-1A images from 2015 to 2017. The results indicate that the densities of PTs extracted on the two bridges increased by about 40% using the new approach, and incorrect noise signals are removed. Moreover, the mechanical properties of different bridge components can be evaluated through the analysis of their structural stress and time-series displacements, helping to decrease the false-alarm/miss-detection rates of InSAR-based structural risk identification. The bridge deformation is correlated with the temperature variation when the temperature difference is large ($\ge$10 °C), but no longer dominated by thermal dilation when the temperature difference is less than 10 °C due to the influence of environmental effects.

跨海桥梁的变形监测和风险识别对于减轻危害和防止人员生命财产损失至关重要。星基合成孔径雷达干涉测量（InSAR）技术可检测毫米级变形，在跨海桥梁安全监测中显示出独特优势。然而，现有的InSAR方法仅基于相干指数提取点状目标（PTs），而忽略了对多个SAR非相干信息的分析以及桥梁前背景散射特征的差异，导致密度低、精度低。跨海大桥上的 PT。此外，大多数基于 InSAR 的研究根据变形测量识别结构风险，而没有充分考虑不同结构部件的各种安全变形范围，导致在跨海桥梁结构风险识别中的高误报/漏检率。为了解决这些问题，开发了一种结构知识-InSAR 集成方法，用于跨海桥梁的高精度变形监测和可靠的风险识别。首先，分析并应用桥梁结构的SAR非相干信息和前景-背景散射特性，以提高可提取PT的密度并去除不正确的噪声信号。然后，将桥梁结构力学模型与InSAR时间序列位移相结合，分析不同桥梁构件力学性能退化情况，提高基于InSAR结构风险识别的可靠性。该方法使用 2011 年至 2012 年的 TerraSAR-X 和 COSMO-SkyMed 图像以及 2015 年至 2017 年的 Sentinel-1A 图像应用于昂船洲大桥和青马大桥。 结果表明，在两座桥梁上提取的 PT 密度使用新方法增加了约 40%，并去除了不正确的噪声信号。此外，可以通过分析不同桥梁构件的结构应力和时间序列位移来评估不同桥梁构件的力学性能，有助于降低基于 InSAR 结构风险识别的误报/漏检率。当温差较大时，桥梁变形与温度变化相关（结果表明，使用新方法在两个桥上提取的 PT 密度增加了约 40%，并且去除了不正确的噪声信号。此外，可以通过分析不同桥梁构件的结构应力和时间序列位移来评估不同桥梁构件的力学性能，有助于降低基于 InSAR 结构风险识别的误报/漏检率。当温差较大时，桥梁变形与温度变化相关（结果表明，使用新方法在两个桥上提取的 PT 密度增加了约 40%，并且去除了不正确的噪声信号。此外，可以通过分析不同桥梁构件的结构应力和时间序列位移来评估不同桥梁构件的力学性能，有助于降低基于 InSAR 结构风险识别的误报/漏检率。当温差较大时，桥梁变形与温度变化相关（有助于降低基于 InSAR 结构风险识别的误报/漏检率。当温差较大时，桥梁变形与温度变化相关（有助于降低基于 InSAR 结构风险识别的误报/漏检率。当温差较大时，桥梁变形与温度变化相关（$\ge$10 °C)，但由于环境效应的影响，当温差小于 10 °C 时不再以热膨胀为主。