基于层次非负特征值约束的Yamaguchi分解
doi: 10.3724/SP.J.1146.2012.01381
Yamaguchi Decomposition Based on Hierarchical Nonnegative Eigenvalue Restriction
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摘要: 针对现有Yamaguchi分解的相干矩阵存在不满足非负特征值约束(NER)的问题，该文提出一种基于层次NER的Yamaguchi分解。该文分析得出，NER问题源自于散射功率的过估计，并指出只要解决了余项相干矩阵的NER问题，就能解决所有相干矩阵的NER问题。于是基于非负特征值分解(NNED)，依次建立了抑制散射功率过估计的第1层至第4层NER方法，其中后层的NER方法需要分层次地执行前层的NER方法。第4层NER方法解决了余项相干矩阵的NER问题，进而解决了所有相干矩阵的NER问题。另外，该文还提出比原有NNED效率更高的快速NNED。实验结果表明，所提出的分解方法能显著增强城区的二面角散射功率与抑制城区的体散射功率，并能显著增强海洋区的面散射功率。
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关键词:
- 极化合成孔径雷达 /
- 极化目标分解 /
- Yamaguchi分解 /
- 非负特征值约束 /
- 非负特征值分解(NNED)
Abstract: To solve the issue that coherency matrices of the existing Yamaguchi decompositions do not satisfy Nonnegative Eigenvalue Restriction (NER), Yamaguchi decomposition based on hierarchical NER is proposed. It is derived that the NER problem results from the overestimation of scattering powers, and it is pointed out that if the NER problem of remainder coherency matrix is resolved, the NER problems of all coherency matrices are also resolved. Then, the NER methods of the first layer to the fourth layer are proposed orderly based on NonNegative Eigenvalue Decomposition (NNED) to depress the overestimation of scattering powers. For the NER methods, the posterior-layer NER methods need to hierarchically implement the anterior-layer NER methods. The fourth-layer NER method resolves the NER problem of remainder coherency matrix, so the NER problems of all coherency matrices are also resolved. In addition, the fast NNED more efficient than the existing NNED is derived. The experiment result shows that the proposed decomposition can markedly enhance double-bounce scattering power and reduce volume scattering power for urban areas, and enhance surface scattering power for ocean areas. -
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