Toward Retrieving Discontinuous Deformation of Bridges by MTInSAR With Adaptive Segmentation

The application of multitemporal interferometric synthetic aperture radar (MTInSAR) technology in bridge structural health monitoring often encounters considerable challenges due to the intricate nature of bridge structures. Notably, the thermal expansion and contraction (TEC) of bridges can lead to prominent interferometric phase jumps at the expansion joints. When the magnitude of the phase jump exceeds
$\pi $
, the continuity assumption required for phase unwrapping is no longer valid. Consequently, classical phase unwrapping methods fail to accurately retrieve bridge deformation. To address this limitation, we propose an adaptive MTInSAR method that can partition the bridge into independent segments and concurrently estimate deformation from multiple reference points. The algorithm first identifies expansion joint locations using a mean square error threshold. Subsequently, reference point selection and segmental phase unwrapping are performed to derive displacement time series of persistent scatterers (PSs), where the mechanical properties of the bridge structure are considered. We validate the effectiveness of the method using 23 TerraSAR-X (TSX) images of the Shanghai Yangtze River Bridge. The results demonstrate the successful detection of expansion joints and reliable phase unwrapping in PS subnetworks. Moreover, a comparative analysis with the classical minimum cost flow (MCF) method highlights the superior adaptability and reliability of the proposed approach. Finally, threshold values for triggering conditions when phase jumps occur are quantified. The proposed work will enhance the robust monitoring of bridge motions, safeguarding the structural health of bridges.