Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation

A stack of images is a prerequisite for the multi-temporal interferometric synthetic aperture radar (MT-InSAR) due to wrapped nature phase. Although SBAS technique can relieve requirement amount SAR data, dozens acquisitions could be regarded as minimum requirement. However, limitation imaging capability spaceborne system, available data acquired from only one sensor often not enough satisfy phase unwrapping based on Nyquist sampling assumption. Fortunately, there sometimes may more than stack, that is, stacks different systems. In this study, we propose methodology detect ground deformation by combining multiple satellite systems MT-InSAR analysis. First, low-pass estimated time series with low spatial resolution and long wavelengths such ENVISAT ASAR (ASAR). This information then incorporated into processing high short wavelength, TerraSAR-X (TSX). Specifically, will subtracted each differential interferogram generated short-wavelength images, rest analysis double-differentiation interferograms. Then, residual calculated these interferograms together forms full deformation. As principal component has already been subtracted, gradient those double-differentiated smooth facilitate unwrapping. Between January 2009 September 2010, 14 11 TSX Tianjin, China are selected test data. root means square error (RMSE) 9.1 mm/year achieved while 3.7 images. an RMSE 1.6 when integrating The experiments show proposed method effectively