Assimilation of GPS-Derived Atmospheric Propagation Delay in DInSAR Data Processing

Abstract

Microwave radiation is almost insensitive in terms of power attenuation to the presence of atmosphere; the atmosphere is however an error source in repeat pass interferometry due to propagation delay variations. This effect represents a main limitation in the detection and monitoring of weak deformation patterns in differential interferometric Synthetic Aperture Radar (DInSAR), especially in emergency conditions. Due to the wavelength reduction current, X-Band sensors are even more sensitive to such error sources: procedures adopted in classical advanced DInSAR for atmospheric filtering may fail in the presence of higher revisiting rates. In this work, we show such effect on data acquired by the COSMO-SkyMed constellation. The dataset has been acquired with very high revisiting rates during the emergency phase. This feature allows clearly showing the inability of standard filtering adopted in common processing chains in handling seasonal atmospheric delay variations over temporal intervals spanning periods shorter than 1 year. We discuss a procedure for the mitigation of atmospheric propagation delay (APD) that is based on the integration of data of GPS systems which carries out measurements with large observation angles diversity practically in continuous time. The proposed algorithm allows a robust assimilation of the GPS atmospheric delay measurements in the multipass DInSAR processing and found on a linear approximation with the height of the atmospheric delay corresponding to a stratified atmosphere. Achieved results show a significant mitigation of the seasonal atmospheric variations.