Airport runway roughness evaluation using TCP-InSAR technology
Haidong Zhao, Yu Tian, Junzhe Wang, Jingfu Chen, Bao Mi, Xinwei Jiang
Abstract
Runway roughness evaluation plays a vital role in maintaining operational efficiency and guiding maintenance planning for airport ground operations. Conventional measurement methods often suffer from limited spatial coverage, low efficiency, and significant operational disruptions. This study presents an Interferometric Synthetic Aperture Radar (InSAR) approach for runway roughness assessment that achieves wide-area, efficient, and non-intrusive evaluation. The Temporarily Coherent Point InSAR algorithm effectively mitigates specular reflection from runway surfaces, delivering high-precision time-series vertical displacement data. Subsequently, the Nonlinear PCA-Co Kriging method integrates InSAR observations with levelling Digital Elevation Model data, followed by interpolation and resampling to create a high-resolution 3D runway elevation model. From those model, longitudinal profiles of the runway centerline and 6 meters east/west were extracted for Boeing Bump Index (BBI) calculation. Results demonstrate that the Nonlinear PCA-Co Kriging method surpasses traditional Original Kriging and Co-Kriging techniques in detecting elevation changes. The computed Boeing Bump Index shows excellent agreement with vehicle-mounted measurements (minimum correlation coefficient of 0.94, maximum mean absolute error of 0.025 BBI, standard deviation of 0.028 BBI), validating the method's reliability for runway roughness monitoring.