High Speed Railway Deformation Monitoring and Analysis Considering PS-InSAR Precise Positioning

This study proposes an adaptive localization correction method that integrates track geometric features to address spatial alignment deviations in deformation monitoring of high-speed railways using PS-InSAR technology. First, traditional buffer methods for complex linear regions are optimized using Melkman’s convex hull algorithm to refine railway contour morphology, resolving spatial gaps and overlaps. Second, a dynamic buffer model incorporating radar incidence angles and track elevation data is developed to mitigate geometric distortions through adaptive threshold adjustments, ensuring precise association between scatterers and track structures. Finally, spatial matching accuracy is enhanced via K-nearest neighbor (KNN) search and iterative completion mechanisms, with hierarchical clustering applied to remove outliers. Validated in the Wu-Guang High-Speed Railway corridor, the method achieves sub-meter positioning accuracy for PS points. Cross-validation with leveling data reveals vertical displacement RMSE below 1.6 mm, confirming the method’s reliability. This approach provides high-precision deformation field reconstruction and risk early warning capabilities for linear infrastructure systems, offering substantial engineering value for optimizing intelligent rail transit operation and maintenance frameworks.