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

Huaping Xu, Guobing Zeng, Wei Liu, Yuan Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Multitemporal synthetic aperture radar interferometry (MTInSAR) is an efficient geodetic tool for Earth surface displacement measurement, and the polarimetric capability of current and upcoming SAR satellites offers a new opportunity to further improve MTInSAR phase series estimation. However, none of the 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 the performance evaluation of multipolarimetric MTInSAR phase series estimation in practical scenarios where the RMSE is not feasible any more. The 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 interchannel interference than existing methods.

Original languageEnglish
Article number5202913
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume61
DOIs
Publication statusPublished - Feb 2023

Keywords

  • Cramer-Rao lower bound (CRLB)
  • maximum likelihood estimation (MLE)
  • multipolarimetric phase linking
  • multitemporal synthetic aperture radar interferometry (MTInSAR)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • General Earth and Planetary Sciences

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