Title | ||
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Seven-Component Model-Based Decomposition for PolSAR Data with Sophisticated Scattering Models |
Abstract | ||
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Due to incomprehensive and inaccurate scattering modeling, the state-of-the-art polarimetric synthetic aperture radar (PolSAR) model-based target decompositions are incapable of effectively depicting the scattering mechanism of obliquely oriented urban areas. In this paper, a seven-component model-based decomposition scheme is proposed by constructing several sophisticated scattering models. First, an eigenvalue-based obliquely-oriented dihedral scattering model is presented to reasonably distribute the co-polarization and cross-polarization scattering powers in obliquely oriented urban areas, thus accurately characterizing the urban scattering. Second, the +/- 45 degrees oriented dipole and +/- 45 degrees quarter-wave reflector scattering models are incorporated for the purpose of accounting for the real and imaginary components of the T-13 element in the coherency matrix so as to fully utilize polarimetric information. Finally, according to their mathematical forms, several strategies for model parameter solutions are designed, and the seven-component decomposition is fulfilled. Experimental results conducted on different PolSAR data demonstrate that the proposed method considerably improves the PolSAR scattering interpretation in a more physical manner compared to other existing model-based decomposition, which can be applied for urban area detection, classification, and other urban planning applications. |
Year | DOI | Venue |
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2019 | 10.3390/rs11232802 | REMOTE SENSING |
Keywords | DocType | Volume |
polarimetric synthetic aperture radar (PolSAR),seven-component model-based decomposition,obliquely oriented dihedral scattering model,+/- 45 degrees oriented dipole scattering model,+/- 45 degrees oriented quarter-wave reflector scattering model | Journal | 11 |
Issue | Citations | PageRank |
23 | 0 | 0.34 |
References | Authors | |
0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Hui Fan | 1 | 0 | 0.68 |
Sinong Quan | 2 | 0 | 1.69 |
Dahai Dai | 3 | 9 | 5.29 |
XueSong Wang | 4 | 171 | 32.83 |
ShunPing Xiao | 5 | 95 | 21.88 |