MLE-MPPL: A Maximum Likelihood Estimator for Multipolarimetric Phase Linking in MTInSAR

Abstract

Multi-Temporal Synthetic Aperture Radar Interferometry (MTInSAR) is an efficient geodetic tool for earth surface displacement measurement, and the polarimetric capability of current and upcoming Synthetic Aperture Radar (SAR) satellites offers a new opportunity to further improve MTInSAR phase series estimation. However, none of existing estimators for multipolarimetric MTInSAR phase series of distributed scatters (DSs) is derived under the minimum root mean square error (RMSE) criterion. In this work, a maximum likelihood estimator for multipolarimetric phase linking (MLE-MPPL) is proposed and the corresponding Cramer-Rao lower bound (CRLB) is also derived by modeling the polarimetric interferometric coherence matrix as the Kronecker product of polarimetric coherence matrix and interferometric coherence matrix. In addition, a new metric called Pol-detR is proposed for performance evaluation of multipolarimetric MTInSAR phase series estimation in practical scenarios where the RMSE is not feasible any more. Experimental results based on both simulated and real data show that the proposed MLE-MPPL achieves the best estimation performance and is more robust against inter-channel interference than existing methods.