Demonstration and Analysis of an Extended Adaptive General Four-Component Decomposition

The overestimation of volume scattering is an essential shortcoming of the model-based polarimetric synthetic aperture radar (PolSAR) target decomposition method. It is likely to affect the measurement accuracy and result in mixed ambiguity of the scattering mechanism. In this article, an extended adaptive four-component decomposition method with multiple thresholds is proposed. First, the orientation angle compensation is applied to the coherency matrix, and artificial areas are extracted as the basis for selecting the decomposition method. Second, for the decomposition of artificial areas, one of the two complex unitary transformation matrices of the coherency matrix is selected according to the wave anisotropy (
${A_w}$
). In addition, the branch condition that is used as a criterion for the hierarchical implementation decomposition is the ratio of the correlation coefficient (
${R_{\text{cc}}}$
). Finally, the selected unitary transformation matrix and the discriminative threshold are used to determine the structure of the selected volume scattering models, which are more effective to adapt to various scattering mechanisms. In this article, the performance of the proposed method is evaluated on GaoFen-3 full PolSAR datasets for various time periods and regions. The experimental results demonstrate that the proposed method can effectively represent the scattering characteristics of the ambiguous regions, and the oriented building areas can be well discriminated as dihedral or odd-bounce structures.