Phase Linking in Multipolarimetric Multibaseline Joint Scatterer Interferometric Synthetic Aperture Radar

Time-series interferometric synthetic aperture radar technology can monitor surface deformation with millimeter-level accuracy. To overcome the low point density associated with permanent scatterer technology, phase linking (PL) algorithms are used in distributed scatterer interferometry to enhance measurement capabilities significantly. Furthermore, the use of multipolarimetric data can improve the quality of equivalent single-master interferometric phases. In this study, a polarimetric joint scatterer (JS) interferometric synthetic aperture radar algorithm is proposed to perform PL on multipolarimetric multibaseline (MPMB) data. First, an MPMB JS covariance matrix is estimated on the basis of modeled JS data and statistically homogeneous pixels identified by a proposed polarimetric time-series likelihood ratio test. Then, we propose the joint sum of Kronecker product method, which decomposes the MPMB JS covariance matrix to separate dominant scattering mechanisms. After performing joint sum of Kronecker product decomposition, we derive the PL algorithm to obtain equivalent single-master interferometric phases under the frameworks of array signal processing and maximum likelihood estimation. The proposed polarimetric JS interferometric synthetic aperture radar algorithm further enhances the density of measurement points, thus improving the quality of phase optimization. Finally, the feasibility of the proposed method is verified through simulations and experiments involving real data from ALOS-2.