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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Maximum likelihood estimation of K distribution parameters for SAR data
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Maximum likelihood estimation of K distribution parameters for SAR data

机译：SAR数据K分布参数的最大似然估计

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The K distribution has proven to be a promising and useful model for backscattering statistics in synthetic aperture radar (SAR) imagery. However, most studies to date have relied on a method of moments technique involving second and fourth moments to estimate the parameters of the K distribution. The variance of these parameter estimates is large in cases where the sample size is small and/or the true distribution of backscattered amplitude is highly non-Rayleigh. The present authors apply a maximum likelihood estimation method directly to the K distribution. They consider the situation for single-look SAR data as well as a simplified model for multilook data. They investigate the accuracy and uncertainties in maximum likelihood parameter estimates as functions of sample size and the parameters themselves. They also compare their results with those from a new method given by Raghavan (1991) and from a nonstandard method of moments technique; maximum likelihood parameter estimates prove to be at least as accurate as those from the other estimators in all cases tested, and are more accurate in most cases. Finally, they compare the simplified multilook model with nominally four-look SAR data acquired by the Jet Propulsion Laboratory AIRSAR over sea ice in the Beaufort Sea during March 1988. They find that the model fits data from both first-year and multiyear ice well and that backscattering statistics from each ice type are moderately non-Rayleigh. They note that the distributions for the data set differ too little between ice types to allow discrimination based on differing distribution parameters.
机译：K分布已被证明是合成孔径雷达（SAR）图像中反向散射统计数据的有希望和有用的模型。但是，迄今为止，大多数研究都依赖于涉及第二和第四矩的矩量技术来估计K分布的参数。在样本量较小和/或反向散射幅度的真实分布高度非瑞利的情况下，这些参数估计值的方差较大。本文作者将最大似然估计方法直接应用于K分布。他们考虑了单视SAR数据的情况以及多视数据的简化模型。他们调查了最大似然参数估计值的准确性和不确定性，这些估计值是样本大小和参数本身的函数。他们还将他们的结果与Raghavan（1991）提出的新方法和非标准矩量法的结果进行了比较。在所有测试情况下，最大似然参数估计值都至少与其他估计值的准确性相同，并且在大多数情况下更准确。最后，他们将简化的多视场模型与喷气推进实验室AIRSAR在1988年3月在波弗特海的海冰上获得的名义上的四视场SAR数据进行了比较。他们发现该模型适合于第一年和多年冰场的数据，每种冰类型的反向散射统计数据均为中等非瑞利分布。他们注意到，不同冰类型之间数据集的分布差异太小，无法根据不同的分布参数进行区分。

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