Joint-scatterer processing for time-series InSAR

The first-generation time-series synthetic aperture radar interferometry (TSInSAR) technique persistent-scatterer (PS) InSAR has been proven effective in ground deformation measurement over areas with high reflectivity by taking advantage of coregistered temporally coherent pointwise scatterers. In order to increase the spatial density of measurement points and quality of displacement time series over moderate reflectivity scenes, a second-generation TSInSAR called SqueeSAR was developed to extract displacement information from both PSs and distributed scatterers, by taking into account their temporal coherence and their spatial statistical behavior. In this paper, we propose a new second-generation TSInSAR, which is referred to as joint-scatterer (JS) InSAR, to measure the line-of-sight surface displacement using the neighboring pixel stacks. A novel goodness-of-fit testing approach is proposed to analyze the similarity between two JS vectors based on time-series likelihood ratios. By taking advantage of the proposed test, a new spatially adaptive filter is developed to estimate the covariance matrix. Based on the estimated covariance matrix, the projection of the joint signal subspace onto the corresponding joint noise subspace is applied to retrieve phase history. With coherence information of neighboring pixel stacks, JSInSAR is able to provide reliable geophysical parameters in the presence of large coregistration errors. The effectiveness of the proposed technique is verified with a time series of high-resolution SAR data from the TerraSAR-X satellite.