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Ocean wind retrieval from polarimetric sar observations

机译:从极化SAR观测中获取海洋风

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Coastal wind are strongly influenced by topology, the discontinuity between the land and sea surface, wind assessment from remote sensing in such a complex area remains challenge. Space-borne scatterometer does not provide any information about the coastal wind field, as the coarse spatial resolution hampers the radar backscattering. Synthetic aperture radar (SAR) with a high spatial resolution and all-weather observation abilities has become one of the most important ways of ocean wind retrieval, especially in the coastal area. Conventional ways of wind field retrieval from SAR, however, are always need wind direction as initial information, such as the wind direction from numerical weather prediction models (NWP) which may not match the time of SAR image acquiring. Fortunately, the fully polarimetric observations of SAR make the independent wind retrieval from SAR images become reality. In this paper, a new method of using co-polarization backscattering coefficients from fully polarimetric SAR observations up to polarimetric correlation backscattering coefficients which are acquired from the conjugate product of co-polarization backscatter and cross-polarization backscatter is proposed to obtain the coastal wind field. Co-polarization backscattering coefficients and polarimetric correlation backscattering coefficients are obtained form Radarsat-2 single-look complex (SLC) data, the maximum likelihood estimation is used to gain the initial results followed by the coarse spatial filtering and fine spatial filtering. Wind direction accuracy of the final inversion results ±10.67° with a wind speed accuracy of ±0.32m/s. In comparison to the previous methods, this article based on the SAR data itself to obtain the wind vectors and did not need external wind directional information. High spatial resolution and high accuracy are the most important features of this article since the full use of fully polarimetric observations which contained more information about the objects. This article is a useful attempt to the work of independent SAR wind retrieval. The experimental results show that it is feasible to employ the co-polarimetric backscattering coefficients and the polarimetric correlation backscattering coefficients for coastal wind field retrieval.
机译:沿海风受到地形的强烈影响,陆地和海面之间的不连续性,在这样一个复杂区域中通过遥感进行风能评估仍然是一个挑战。星载散射仪不提供有关沿海风场的任何信息,因为粗糙的空间分辨率会阻碍雷达的反向散射。具有高空间分辨率和全天候观测能力的合成孔径雷达(SAR)已成为海洋风检索的最重要方法之一,特别是在沿海地区。然而,从SAR检索风场的常规方法始终需要将风向作为初始信息,例如来自数值天气预报模型(NWP)的风向可能与SAR图像的获取时间不匹配。幸运的是,SAR的全极化观测使从SAR图像获得独立的风回波成为现实。本文提出了一种利用全极化SAR观测中的共极化反向散射系数和从共极化反向散射与交叉极化反向散射共轭积获得的极化相关反向散射系数来获得海岸风场的新方法。 。从Radarsat-2单视复数(SLC)数据获得同极化反向散射系数和极化相关反向散射系数,使用最大似然估计获得初始结果,然后进行粗略空间滤波和精细空间滤波。最终反演的风向精度为±10.67°,风速精度为±0.32m / s。与以前的方法相比,本文基于SAR数据本身​​来获取风向矢量,不需要外部风向信息。高空间分辨率和高精度是本文的最重要特征,因为充分利用了全极化观测资料,该观测资料包含有关物体的更多信息。本文是对独立的SAR风取回工作的有益尝试。实验结果表明,利用共极化背向散射系数和极化相关背向散射系数进行沿海风场反演是可行的。

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