Deformation Monitoring of Truss Structure Bridge With Time-Series InSAR Analysis

Abstract

Time-series InSAR is an advanced technology for real-time monitoring and precise analysis of object deformation. However, large-span steel truss structure bridges have complex bridge structures and deformation forms, which make it difficult for the traditional persistent scatterer interferometry (PSI) method to realize the precise detection of their deformation, resulting in a series of limitations. In order to solve these problems, an improved PSI method is proposed in this article, which is first to carry out preliminary elevation measurement by a small temporal baseline, use the preliminary elevation results to PS-arcs construction based on 3-D spatial network, and utilize the optimal model coherence coefficient adaptive selection based on constant false alarm rate to carry out the parameter estimation so as to realize the accurate monitoring of deformation of large-span steel truss structure bridges. In this article, 24 ascending CSK stripmaps are used to monitor the deformation of Dongting Lake Bridge of the Menghua Railway, and the monitoring results show that the method not only realizes the accurate detection of deformation of large-span steel truss structure bridges but also improves the accuracy and robustness of parameter estimation. The results show that the proposed method improves the accuracy of deformation parameter estimation by comparing with the deformation parameters solved by the traditional method, and the method reduces the average residual phase standard deviation by 10%, which provides the experience and reference for the deformation monitoring of similar bridges.

Keywords

• 3-D persistent scatterer (PS) network
• bridge deformation monitoring
• constant false alarm rate (CFAR)
• persistent scatterer interferometry (PSI)