An improved four-component decomposition with distributed double-bounce scattering model

This paper proposes an improved four-component scattering decomposition scheme with modified double-bounce scattering model for the analysis of polarimetric synthetic aperture radar (POLSAR) data. In the Yamaguchi decomposition, it occurs occasionally for some pixels with negative surface scattering power Ps and/or negative diplane scattering power Pd because the whole HV cross-polarized component is assigned to volume scattering due to vegetation; and it is also difficult to discriminate man-made buildings not orthogonal to the radar LOS from vegetation. In advance the conditions of the emergence of negative powers in the Yamaguchi decomposition are given out, and three corresponding processing methods adopted in many improved four-component target decompositions are reviewed in the paper. Then the expression of the coherency matrix of distributed dielectric dihedral corner reflectors is derived. The expression demonstrates that distributed dielectric dihedral corner reflectors also will generate HV cross-polarized component. The new target decomposition utilizes the new double bounce model of distributed dielectric dihedral corner reflectors instead of the original one adopted by the Freeman and Yamaguchi decompositions. In order to solve the new decomposition, we introduce normalize circular-pol correlation coefficients to characterize the percentage of HV scattering component generated by distributed dielectric dihedral corner reflectors. An airborne L band quad-pol data acquired by DLR ESAR sensor over Oberpfaffenhoffen in German are applied to the improved decomposition scheme. Experimental results demonstrate that the new decomposition method can reduce the pixels with negative powers and obtain correct scattering mechanisms of non-reflection structures not paralleled to the flight path.

[1]  Jian Yang,et al.  Four-Component Decomposition of Polarimetric SAR Images With Deorientation , 2011, IEEE Geoscience and Remote Sensing Letters.

[2]  Eric Pottier,et al.  A review of target decomposition theorems in radar polarimetry , 1996, IEEE Trans. Geosci. Remote. Sens..

[3]  Jian Yang,et al.  Three-Component Model-Based Decomposition for Polarimetric SAR Data , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Jakob J. van Zyl,et al.  Adaptive Model-Based Decomposition of Polarimetric SAR Covariance Matrices , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Hiroyoshi Yamada,et al.  A four-component decomposition of POLSAR images based on the coherency matrix , 2006, IEEE Geoscience and Remote Sensing Letters.

[6]  W. Holm,et al.  On radar polarization mixed target state decomposition techniques , 1988, Proceedings of the 1988 IEEE National Radar Conference.

[7]  Jakob J. van Zyl,et al.  A General Characterization for Polarimetric Scattering From Vegetation Canopies , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Thomas L. Ainsworth,et al.  Polarimetric SAR data compensation for terrain azimuth slope variation , 2000, IEEE Trans. Geosci. Remote. Sens..

[9]  J. S. Lee,et al.  Polarimetric SAR characterization of man-made structures in urban areas using normalized circular-pol correlation coefficients , 2008 .

[10]  Seiho Uratsuka,et al.  Polarimetric SAR Image Analysis Using Model Fit for Urban Structures , 2005, IEICE Trans. Commun..

[11]  Hiroyoshi Yamada,et al.  Four-Component Scattering Power Decomposition With Rotation of Coherency Matrix , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[12]  I. Hajnsek,et al.  Polarization orientation effects in urban areas on SAR data , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[13]  Hong Zhang,et al.  Improved Four-Component Model-Based Target Decomposition for Polarimetric SAR Data , 2012, IEEE Geoscience and Remote Sensing Letters.

[14]  Stephen L. Durden,et al.  A three-component scattering model for polarimetric SAR data , 1998, IEEE Trans. Geosci. Remote. Sens..

[15]  Xi Chen,et al.  Four-Component Model-Based Decomposition of Polarimetric SAR Data for Special Ground Objects , 2012, IEEE Geoscience and Remote Sensing Letters.

[16]  Hiroyoshi Yamada,et al.  POLSAR Image Analysis of Wetlands Using a Modified Four-Component Scattering Power Decomposition , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Hiroyoshi Yamada,et al.  Four-component scattering model for polarimetric SAR image decomposition , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Yoshio Yamaguchi,et al.  Four-Component Scattering Power Decomposition With Extended Volume Scattering Model , 2012, IEEE Geoscience and Remote Sensing Letters.