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Estimating the effective number of looks in interferometric SAR data

机译：估算干涉SAR数据中的有效视线数

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The probability density function (pdf) of the multi-look interferometric phase between two complex synthetic aperture radar (SAR) images is parameterized by the number of looks and the complex correlation coefficient. In practice, adjacent pixels in a real SAR interferogram, are statistically dependent due to filtering, and hence, the number of looks is usually smaller than the number of samples averaged. It has been shown that compensation with an effective number of looks, rather than an intractable rederivation of the pdf, can account for the statistical dependence. This paper addresses the challenge of how to determine a suitable value for the effective number of looks. It is shown that an optimum value can be found via a maximum-likelihood estimator (MLE) based on the interferometric phase pdf. However, since such an MLE is computationally intensive and numerically unstable, an estimator based on the method of moments (MoM) possessing similar fidelity is proposed. MoM is fast and robust and can be used in operational applications, such as determining constant false alarm rate (CFAR) detection thresholds for moving-target detection in SAR along-track interferometry.
机译：两个视差合成孔径雷达（SAR）图像之间的多视干涉相的概率密度函数（pdf）由视数和复相关系数来参数化。实际上，由于滤波，实际SAR干涉图中的相邻像素在统计上是相关的，因此外观数量通常小于平均采样数量。已经表明，用有效外观数进行补偿而不是难于重新定义pdf可以解释统计依赖性。本文解决了如何为有效外观数量确定合适的值的挑战。结果表明，可以基于干涉相位pdf通过最大似然估计器（MLE）找到最佳值。然而，由于这种MLE在计算上是密集的并且在数值上是不稳定的，因此提出了一种基于具有相似保真度的矩量法（MoM）的估计器。 MoM快速且强大，可用于操作应用程序，例如确定恒定的虚警率（CFAR）检测阈值，以用于SAR沿轨干涉测量中的移动目标检测。

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