中文摘要：

沿海的风被在土地和海表面之间的拓扑学和断绝强烈影响。从在如此的一个复杂区域的遥感的风评价仍然是挑战。卫星转菠的 scatterometer 不在沿海的风地附近提供任何信息，当粗糙的空间决定妨碍雷达 backscattering。有高空间的分辨率和全天候的观察能力的合成的孔雷达(SAR ) 为海洋风检索成为了最重要的工具之一，特别在沿海的区域。然而，从 SAR 的风域检索的常规方法作为起始的信息要求风方向，例如从数字天气预言模型(NWP ) 的风方向，它不能匹配 SAR 图象获得的时间。幸好， SAR 的测定偏振的观察独自从 SAR 图象启用独立的风检索。以便精确地测量沿海的风地，这份报纸建议从测定偏振的 SAR 观察使用合作极化 backscattering 系数直到测定偏振的关联 backscattering 系数的一个新方法，它从合作极化反散射和跨极化的反散射的 conjugate 产品被获得。合作极化 backscattering 系数和测定偏振的关联 backscattering 系数被获得表格 Radarsat-2 单个看的建筑群(SLC ) data.The 最大值可能性的评价被用来获得列在后面由的起始的结果粗糙的空间过滤并且好空间过滤。最后的倒置结果的风方向精确性与 0.32 m/s 的风速度精确性是 10.67。不同于以前的方法，在这篇文章描述的方法自己利用 SAR 数据获得风向量并且不需要外部风方向性的信息。高空间的分辨率和高精确性是自从完整的测定偏振的观察的使用关于测量的空格包含更多的信息，此处描述的方法的最重要的特征。这篇文章是独立 SAR 风检索的工作的有用增加。试验性的结果此处证明采用 co 测定偏振的 backscattering 系数是可行的，为沿海的风的测定偏振的关联 backscattering 系数回答检索。

英文摘要：

Coastal winds are strongly influenced by topology and discontinuity between land and sea surfaces. Wind assessment from remote sensing in such a complex area remains a 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 tools for ocean wind retrieval, especially in the coastal area. Conventional methods of wind field retrieval from SAR, however, require 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 polarimetric observations of SAR enable independent wind retrieval from SAR images alone. In order to accurately measure coastal wind fields, this paper proposes a new method of using co-polarization backscattering coefficients from polarimetric SAR observations up to polarimetric correlation backscattering coefficients, which are acquired from the conjugate product of co-polarization backscatter and cross-polarization backscatter. 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 is 10.67 with a wind speed accuracy of 0.32 m/s. Unlike previous methods, the methods described in this article utilize the SAR data itself to obtain the wind vectors and do not need external wind directional information. High spatial resolution and high accuracy are the most important features of the method described herein since the use of full polarimetric observations contains more information about the space measured.This article is a useful ad