Abstract
Abstract. There are more unknowns than equations to solve for previous four-component decomposition methods. In this case, the nonnegative power of each scattering mechanism has to be determined with some assumptions and physical power constraints. This paper presents a new decomposition scheme, which models the measured matrix after polarimetric orientation angle (POA) compensation as a linear sum of five scattering mechanisms (i.e., odd-bounce scattering, double-bounce scattering, diffuse scattering, volume scattering, and helix scattering). And the volume scattering power is calculated by a slight modified NNED method, owing to this method considering the external volume scattering model from oblique dihedral structure. After the helix and volume scattering powers have been determined sequentially, the other three scattering powers are estimated by combining the generalized similarity parameter (GSP) and the eigenvalue decomposition. Among them, due to POA compensation, the diffuse scattering induced from a dihedral with a relative orientation of 45º has negligible scattering power. Thus, the new method can be reduced as four-component decomposition automatically. And then the ALOS-2 PolSAR data covering Guiyang City, Guizhou Province, China were used to evaluate the performance of the new method in comparison with some classical decomposition methods (i.e. Y4R, S4R and G4U).
Highlights
Polarimetric target decomposition plays an important role in the interpretation of polarimetric SAR (POLSAR) data. Freeman and Durden (1998) firstly proposed the original threecomponent decomposition, modeling the measured covariance matrix as a linear sum of three physical scattering mechanisms under the reflection symmetry condition
The diffuse scattering mechanism can be ignored so that the new method can be reduced as four-component decomposition automatically
The new method can work as an alternative to four-component decomposition. 4.2 Discussion The advanced four-component decomposition methods (i.e. Y4R, S4R, and G4R) were applied to this PolSAR data
Summary
Polarimetric target decomposition plays an important role in the interpretation of polarimetric SAR (POLSAR) data. Freeman and Durden (1998) firstly proposed the original threecomponent decomposition, modeling the measured covariance matrix as a linear sum of three physical scattering mechanisms (i.e., surface scattering, double-bounce scattering, and volume scattering) under the reflection symmetry condition. Freeman and Durden (1998) firstly proposed the original threecomponent decomposition, modeling the measured covariance matrix as a linear sum of three physical scattering mechanisms (i.e., surface scattering, double-bounce scattering, and volume scattering) under the reflection symmetry condition. There are more unknowns than equations to solve for the existing model-based decomposition (Freeman and Durden, 1998; Yamaguchi et al, 2005; Yajima et al, 2008; An et al, 2010; Yamaguchi et al, 2011; Sato et al, 2012; Singh et al, 2013). In order to determine the powers of the surface and double-bounce scattering mechanisms, the methods should suppose the magnitude of the unknown parameter α in the double-bounce scattering model to be -1 if
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