Perturbation Analysis of Eigenvector-Based Target Decomposition Theorems in Radar Polarimetry
Perturbation Analysis of Eigenvector-Based Target Decomposition Theorems in Radar Polarimetry
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DOI：
10.1109/tgrs.2013.2257802
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发表时间：
2014-04
影响因子：
8.2
通讯作者：
C. López-Martínez;A. Alonso-González;X. Fàbregas
中科院分区：
文献类型：
--
作者：
C. López-Martínez;A. Alonso-González;X. Fàbregas
对极化合成孔径雷达数据的相干矩阵和H/A/α̅参数的特征分解进行了新的统计分析。其目的是克服以前的方法，这些方法阻止了关于样本特征向量的信息的提取或将分析限制在模拟数据上。本文对相干矩阵的本征分解进行了微扰分析，得到了样本本征值及其均值和方差、样本平均熵和各向异性、样本本征向量和样本αI角以及样本平均α角α̅的解析表达式。所有参数都是关于平均样本数的渐近无偏估计。同时还证明了样本特征向量比样本特征值对相干斑的存在具有更强的鲁棒性。最后，给出了一种精确消除熵偏差的简单方法。
A novel analysis of the statistics of the eigendecomposition of the coherency matrix and the H/A/α̅ parameters of polarimetric synthetic aperture radar data is addressed. The objective is to overcome previous approaches that prevented the extraction of information about the sample eigenvectors or restricted the analysis to simulated data. This paper considers a perturbation analysis of the eigendecomposition of the coherency matrix, making it possible to obtain analytical expressions for the sample eigenvalues and their means and variances, the sample mean entropy and anisotropy, the sample eigenvectors and the sample αi angles, as well as for the sample mean alpha angle α̅. All the parameters are shown to be estimated asymptotically non-biased with respect to the number of averaged samples. It is also demonstrated that the sample eigenvectors are more robust than the sample eigenvalues to the presence of speckle. Finally, a simple technique for the precise removal of the entropy bias is presented.