Model-Based Polarimetric SAR Calibration Method Using Forest and Surface-Scattering Targets

This paper proposes a new polarimetric synthetic aperture radar (SAR) (PolSAR) calibration method that applies an incoherent decomposition model to the uncalibrated covariance data measured for the forest and surface and determines the polarimetric distortion matrix (PDM). The Freeman-Durden model is used to express the polarization-dependent signal reflection from and penetration through the forest. Nonlinear equations built for uncalibrated PolSAR data are solved iteratively. This method is applicable to the lower frequency SAR that associates with the polarization-dependent signal penetration through forest canopies. Using the time series Phased-Array-Type L-band SAR (PALSAR) data acquired from the Amazon rainforest for around three years, we confirm that the proposed method succeeds in the PDM estimation and that the calibrated data preserve the polarimetric performance on HH-VV orthogonality, low crosstalks, and ideal polarimetric signature for the corner reflector. This paper also investigates the signal-penetration properties of the forest associated with the L-band SAR.