Interferometric SAR coherence magnitude estimation using second kind statistics
Interferometric SAR coherence magnitude estimation using second kind statistics
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DOI：
10.1109/tgrs.2006.870440
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发表时间：
2006-06
影响因子：
8.2
通讯作者：
R. Abdelfattah;J. Nicolas
中科院分区：
文献类型：
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作者：
R. Abdelfattah;J. Nicolas
相干幅度是干涉合成孔径雷达（干涉合成孔径雷达）应用分析的基本参数。相干幅度估计是有偏的，需要消除偏差。在窗口基础上计算的样本相干幅度估计取决于独立样本的数量和理论相干性。它已被证明，样本相干幅度估计是最大似然之一。它是一个有偏估计，特别是对于低相干值。在本文中，我们提出了一种新的相干幅度估计获得的矩方法使用“第二类统计量”。用于相干性计算的经典方法（具有规则统计）基于概率密度函数（pdf）模型，用于估计用傅立叶变换定义的规则矩（第一类统计）。所提出的方法是基于相同的pdf模型来计算第二类统计定义的梅林变换（对数矩）。因此，它表明，估计的一致性给出的第一个对数矩是更少的偏见。此外，它表明，使用第二类统计量的复相干图（干涉数据）的相干幅度估计是干涉相干的最佳估计程序。与现有的估计量相比，它给出了接近零的最小偏差。开发的估计方法已被应用于从串联欧洲遥感1号和2号卫星干涉测量数据中获得相干测量，这些数据是在突尼斯、法国和尼泊尔的不同地形和各种地面覆盖类型（农田、森林、湖泊、城市地区、海洋）上收集的
Coherence magnitude is a fundamental parameter for the analysis of applications using interferometric synthetic aperture radar (InSAR). The coherence magnitude estimators are biased and need bias removal. The sample coherence magnitude estimation, computed on a window basis, depends on the number of independent samples and theoretical coherence. It has been shown that the sample coherence magnitude estimator is the maximum-likelihood one. It is a biased estimator, especially for low coherence values. In this paper, we present a novel coherence magnitude estimator obtained from the method of moments using "second kind statistics". Classical methods (with regular statistics) for coherence computation are based on a probability density function (pdf) model for estimating regular moments (first kind statistics) defined with the Fourier transform. The proposed approach is based on the same pdf model to compute the second kind statistics defined with the Mellin transform (log-moment). Thus, it is shown that the estimated coherence given by the first log-moment is less biased. Moreover, it is shown that the coherence magnitude estimation from complex coherence maps (interferometric data) using second kind statistics is the optimal estimation procedure of interferometric coherence. It gives the smallest bias near zero comparing with existing estimators. The developed estimation approaches have been applied to obtain coherence measurements from tandem European Remote Sensing 1 and 2 satellite interferometric data, collected over varying terrain with a variety of ground cover types (agriculture field, forest, lake, urban area, sea) in Tunisia, France, and Nepal