REGULARIZATION PARAMETER SELECTION FOR TOMOSAR IMAGING WITH SINGLE AND DUAL POLARIMETRIC OBSERVATIONS

Abstract

Polarimetric focusing techniques for synthetic aperture radar (SAR) tomography (TomoSAR) pursue finding optimal polarization combinations to extract the associated scattering mechanisms and height of reflectors. Regularization approaches like weighted covariance fitting (WCF), implemented in an iterative manner, attain finer resolution than conventional focusing techniques (e.g., Capon). Such approaches normally entail the selection of a regularization parameter and a first estimate of the power spectrum pattern. Regularization parameter selection via L-Curve method requires providing the scattering vector; nonetheless, it may not be always available, especially when not working at full resolution. Manipulations previously done to the data covariance matrix (e.g., pre-summing) must be equivalent in the scattering vector, which may not be at all times feasible. Accordingly, this article suggests modifying the L-Curve method to work exclusively with data covariance matrices. The proposed novel strategy is applied to WCF, considering single and dual channels. Iterations are stopped based on the Akaike information criterion.