Monitoring Deformation along Railway Systems Combining Multi-Temporal InSAR and LiDAR Data

Abstract

Multi-temporal interferometric synthetic aperture radar (MT-InSAR) can be applied to monitor the structural health of infrastructure such as railways, bridges, and highways. However, for the successful interpretation of the observed deformation within a structure, or between structures, it is imperative to associate a radar scatterer unambiguously with an actual physical object. Unfortunately, the limited positioning accuracy of the radar scatterers hampers this attribution, which limits the applicability of MT-InSAR. In this study, we propose an approach for health monitoring of railway system combining MT-InSAR and LiDAR (laser scanning) data. An amplitude-augmented interferometric processing approach is applied to extract continuously coherent scatterers (CCS) and temporary coherent scatterers (TCS), and estimate the parameters of interest. Based on the 3D confidence ellipsoid and a decorrelation transformation, all radar scatterers are linked to points in the point cloud and their coordinates are corrected as well. Additionally, several quality metrics defined using both the covariance matrix and the radar geometry are introduced to evaluate the results. Experimental results show that most radar scatterers match well with laser points and that LiDAR data are valuable as auxiliary data to classify the radar scatterers.

Railway Infrastructure Classification and Instability Identification Using Sentinel-1 SAR and Laser Scanning Data

“…For instance, Ref. [ 28 ] obtained an association of 94% PS by customizing the significance level to 5%, for the high-resolution Radarsat-2 (Extra Fine mode) SAR data. At the end, 3259 PS out of 3328 were geometrically associated with the real objects.…”

“…Reference [ 27 ] showed for medium resolution SAR data such as Sentinel-1 a/b, 2-D positioning could be improved, ranging between decimeter and couple of meters, with CRs. In addition, [ 28 ] showed that using laser scanning data (LiDAR, e.g., AHN3), the Radarsat-2 (Extra Fine mode) derived PS geolocation along a railway line can be improved. This study will further test and evaluate the Sentinel-1 derived PS geolocation improvement aided by laser scanning data.…”

A Review of GPR Application on Transport Infrastructures: Troubleshooting and Best Practices

“…GPR information can also complement other non-destructive load tests, such as a stiffness assessment with a rolling stiffness measurement vehicle [290], a falling weight deflectometer (FWD) [95] and a light FWD [17,95,286,291], a dynamic cone penetrometer [90], a geo endoscopy test [90], [292] and light detection and ranging or laser imaging detection and ranging (LiDAR) [293]. The use of a multi-temporal InSAR (interferometric synthetic aperture radar) for transport infrastructure monitoring has also been significantly increasing during the last few years [294][295][296]. Studies undertaken on railways have shown the potential of the applicability of In-SAR together with GPR, mainly for the detection of causes of track subsidence [297], and to monitor subsidence at the transition zones of railway bridges [298].…”

Monitoring mining-induced subsidence by integrating differential radar interferometry and persistent scatterer techniques

“…To overcome these limitations of classical DInSAR, various multi-temporal InSAR (MTInSAR) approaches have been developed over the last two decades (Ciampalini et al, 2019;F. Hu et al, 2019;Sousa et al, 2011).…”