An Advanced Time-Series InSAR Approach Based on Poisson Curve for Soft Clay Highway Deformation Monitoring
Lingjie Zhu, Xuemin Xing, Yikai Zhu, Wei Peng, Zhihui Yuan, Qing Xia
Abstract
Monitoring surface deformation for highways built on soft clay subgrades is fundamental for understanding the dynamics of the settlement process and preventing the occurrence of safety accidents. Most of the traditional interferometric synthetic aperture radar (InSAR) deformation models for highway monitoring are based on a combination of one or several empirical functions, which ignores the underground mechanism of highway deformation. To overcome this limitation, we proposed an advanced InSAR approach that improved the InSAR deformation model and parameter estimation algorithm for soft clay road deformation monitoring. The improved InSAR deformation model is based on the Poisson curve, which considers the characteristics of the temporal physical deformation evolution of the soft clay. The improved algorithm for the unknown parameter estimation is based on a GARN algorithm, which can solve the parameters with better accuracy by combining the genetic algorithm and the regularized Newton iterative algorithm. To evaluate the better performance for the proposed approach and its feasibility for soft clay highway monitoring, both the simulation and the real data experiments on a soft clay highway in Foshan, China, are performed. The time-series deformation from January 1, 2015 to January 18, 2017, is retrieved, and the temporal deformational characteristics over this area are analyzed, which facilitates a greater understanding of the deformational evolution process of the soft clay highway. The results are verified in terms of the residual high-pass deformation and the final obtained vertical deformation compared with the external leveling measurements, which indicate the greater reliability of our method.