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OCEAN WAVE MEASUREMENTS FROM ENVISAT ASAR DATA USING A PARAMETRIC INVERSION SCHEME

机译:使用参数反演方案根据ENVISAT ASAR数据进行海浪测量

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摘要

A parametric algorithm is presented to estimate two-dimensional ocean wave spectra from ENVISAT ASAR wave mode data on a global scale. The retrieval scheme makes use of prior information taken from numerical wave models. The Partition Rescale and Shift algorithm (PARSA) is based on a partitioning technique, which splits an a priori wave spectrum into its wave system components. Integral parameters of these systems, such as mean direction, mean wavelength, waveheight, and directional spreading are then adjusted iteratively to improve the consistency with the SAR observation. The method takes into account the full nonlinear SAR imaging process and uses a maximum a posteriori approach, which is based on statistical model quantifying the errors of the SAR imaging model, the SAR measurement, and the prior wave spectra. The method is applied to a global data set of ENVISAT ASAR data acquired during the CAL/VAL phase. The benefit of cross spectra compared to conventional symmetric image spectra is demonstrated.
机译:提出了一种参数算法,可从全球范围内从ENVISAT ASAR波浪模式数据估计二维海浪频谱。检索方案利用了从数值波动模型中获取的先验信息。分区重新缩放和平移算法(PARSA)基于分区技术,该技术将先验波谱划分为其波系分量。然后,迭代地调整这些系统的整体参数,例如平均方向,平均波长,波高和方向扩展,以提高与SAR观测的一致性。该方法考虑了整个非线性SAR成像过程,并使用最大后验方法,该方法基于对SAR成像模型,SAR测量和先验波谱的误差进行量化的统计模型。该方法适用于在CAL / VAL阶段获取的ENVISAT ASAR数据的全局数据集。证明了与常规对称图像光谱相比,交叉光谱的好处。

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