Anomaly Detection in Bridges Using Interferometric Synthetic Aperture Radar (InSAR)

Abstract

Structural Health Monitoring (SHM) plays a crucial role in supporting decision-makers by providing vital information on the structural integrity of bridges. Traditional SHM systems typically rely on in-situ sensors, which can be time-consuming to install and vulnerable to failure during extreme weather events. In contrast, Synthetic Aperture Radar Interferometry (InSAR), leveraging active radar sensors mounted on satellites, has emerged as a promising remote sensing alternative. This technique enables the monitoring of any structure visible from the satellite’s orbit, eliminating the need for on-site sensor installation. Furthermore, depending on the availability of satellite imagery, InSAR allows for retrospective analysis of structural behavior. Historical displacement data can be used to detect anomalous trends, potentially serving as an early warning for hazardous structural conditions. This paper presents an anomaly detection procedure based on InSAR displacement time series. The proposed method is applied to a riverine bridge that collapsed in 2023. The displacement datasets are sourced from the European Ground Motion Service (EGMS), which utilizes Sentinel-1 satellite imagery.