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The Cramér-Rao bound and the optimal parameter estimation method of internal waves in SAR images

机译:SAR图像内波的Cramér-Rao界和最优参数估计方法

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Parameters estimation of internal waves is one of the most important applications of oceanic synthetic aperture radar (SAR) images. Several methods are widely applied to estimate internal waves parameters such as wavelet analysis method, curve fitting method and empirical mode decomposition (EMD) method. Most of these methods suppose the signals processed are affected by the additive random noise. However, the multiplicative noise model of SAR images is not applied to these methods. The result is that these methods could not reach the Cramér-Rao bound (CRB). This paper assumes that SAR images are affected by speckle noise, and take the speckle signal described by a gamma distribution as an example. In this model, this paper derives the CRB for internal waves parameters estimation. Based on the multiplicative noise model and the CRB, this paper proposes an optimal parameters estimation method of internal waves, and the results could reach the CRB. The real image experiments can prove that the proposed method is more accurate and effective than other methods.
机译:内部波的参数估计是海洋合成孔径雷达(SAR)图像的最重要应用之一。小波分析法,曲线拟合法和经验模态分解(EMD)法等多种方法被广泛地用于估计内波参数。这些方法大多数假设处理的信号受累加随机噪声的影响。但是,SAR图像的乘性噪声模型不适用于这些方法。结果是这些方法无法达到Cramér-Rao界(CRB)。本文假设SAR图像受斑点噪声的影响,以伽马分布描述的斑点信号为例。在该模型中,本文推导了用于内部波参数估计的CRB。基于乘性噪声模型和CRB,提出了一种优化的内波参数估计方法,其结果可以达到CRB。真实图像实验可以证明所提出的方法比其他方法更加准确,有效。

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