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Multipolarimetric Synthetic Aperture Radar (SAR) interferometric phase optimization and phase series estimation have received a lot of attentions recently from the polarimetry SAR interferometry (PolInSAR) community. In this paper, a maximum likelihood estimation (MLE) method for the interferometric coherence matrix (ICM) is proposed, which is further applied to both interferometric phase optimization and phase series estimation. By modelling the PolInSAR coherence matrix as the Kronecker product of the polarimetric coherence matrix (PCM) and ICM, the MLE of ICM under complex circular Gaussian distribution hypothesis is acquired through an alternate iterative optimization method. In addition, it is theoretically proved in this paper that the two state-of-the-art methods, i.e., the TP (total power) method and the MLE-MPPL method, are suboptimal compared to the proposed method regarding the MLE of ICM. Numerical experiments are conducted on simulated fully polarimetric data, airborne fully polarimetric E-SAR data and spaceborne dual polarimetric Sentinel-1A data, to confirm the effectiveness and superiority of the proposed method.

An MLE of Interferometric Coherence Matrix and Its Applications in Multipolarimetric Interferometric Phase Optimization and Phase Series Estimation