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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Wind-Vector Estimation for RADARSAT-1 SAR Images: Validation of Wind-Direction Estimates Based Upon Geometry Diversity
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Wind-Vector Estimation for RADARSAT-1 SAR Images: Validation of Wind-Direction Estimates Based Upon Geometry Diversity

机译：RADARSAT-1 SAR图像的风向矢量估计：基于几何分集的风向估计的验证

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摘要

In this letter, a new wind-vector algorithm is presented that uses radar backscatter sigma0 measurements at two adjacent subscenes of RADARSAT-1 synthetic aperture radar (SAR) images, with each subscene having slightly different geometry. Resultant wind vectors are validated using in situ buoy measurements and compared with wind vectors determined from a hybrid wind-retrieval model using wind directions determined by spectral analysis of wind-induced image streaks and observed by colocated QuikSCAT measurements. The hybrid wind-retrieval model consists of CMOD-IFR2 [applicable to C-band vertical-vertical (VV) polarization] and a C-band copolarization ratio according to Kirchhoff scattering. The new algorithm displays improved skill in wind-vector estimation for RADARSAT-1 SAR data when compared to conventional wind-retrieval methodology. In addition, unlike conventional methods, the present method is applicable to RADARSAT-1 images both with and without visible streaks. However, this method requires ancillary data such as buoy measurements to resolve the ambiguity in retrieved wind direction
机译：在这封信中，提出了一种新的风矢量算法，该算法在RADARSAT-1合成孔径雷达（SAR）图像的两个相邻子场中使用雷达反向散射sigma0测量，每个子场的几何形状略有不同。使用原位浮标测量结果风矢量，并将其与从混合风力取回模型确定的风矢量进行比较，该模型使用风向（通过风致图像条纹的频谱分析确定）并通过并置的QuikSCAT测量来观察。混合风采模型由CMOD-IFR2 [适用于C波段垂直-垂直（VV）极化]和根据Kirchhoff散射的C波段共极化比率组成。与传统的取风方法相比，该新算法在RADARSAT-1 SAR数据的风矢量估计中显示出更高的技巧。另外，与常规方法不同，本方法适用于具有和不具有可见条纹的RADARSAT-1图像。但是，此方法需要辅助数据（例如浮标测量）来解决检索到的风向中的歧义

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