Statistical Regularization for TomoSAR Imaging with Multiple Polarimetric Observations

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 16; pp. 1 - 25
• Main Authors: Martin-del-Campo-Becerra, Gustavo Daniel, Torres-Garcia, Eduardo, Torres-Roman, Deni Librado, Serafin-Garcia, Sergio Alejandro, Reigber, Andreas
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Backscatter; Covariance matrices; Data acquisition; Focusing; Inverse problems; Iterative methods; Physical properties; Polarimetric synthetic aperture radar (PolSAR); Polarimetry; Radar polarimetry; Reflectors; Regularization; SAR (radar); SAR tomography (TomoSAR); Scattering; statistical regularization; Statistics; Synthetic aperture radar; Tomography; weighted covariance fitting (WCF)
• ISSN: 1939-1404; 2151-1535
• DOI: 10.1109/JSTARS.2023.3310211

The polarimetric versions of focusing techniques for synthetic aperture radar (SAR) tomography (TomoSAR), apart from estimating the pseudo-power and retrieving the height of reflectors from the recovered local maxima, allow extracting the associated scattering mechanisms. Additionally, scattering patterns can be examined by means of polarimetric indicators like alpha mean angle, used to associate observables with physical properties of the medium. Aimed at easing the analysis of the scattering processes occurring in the illuminated scene, this article extends the weighted covariance fitting (WCF)-based iterative spectral estimator (WISE) to the polarimetric configuration, called hereafter PolWISE. The addressed technique attains finer resolution than conventional methods like PolCapon, performing suppression of artefacts and ambiguity reduction. PolWISE is a statistical regularization approach, which reduces the TomoSAR inverse problem to the selection of a regularization parameter, chosen via the L-Curve method. Furthermore, being PolWISE an iterative technique, under/over regularization is prevented by terminating the procedure at an appropriate iteration. A stopping rule based on Kullback-Leibler information criterion is employed. The PolWISE algorithm is assessed thoroughly through simulations and experiments on fully polarimetric TomoSAR airborne data at L-band, acquired from an urban scenario.