基于极化与多种纹理特征的高分辨率全极化SAR海面风场反演研究

As the development of high resolution fully polarimetric synthetic aperture radar (SAR), it can offer more polarimetric and texture information for retrieving sea surface wind field. However, the corresponding research on sea surface wind retrieval is still at the preliminary stage. In this study, the problem of "how to use polarimetric and multiple texture features to retrieve sea surface wind field" will be explored. The study will be carried out from the following two aspects. 1) Based on the numerical model of fully polarimetric scattering from wind waves, the relationship between polarimetric parameters and sea surface wind field will be analyzed. The construction method of the fully polarimetric SAR geophysical model function will be searched by fitting model-genetic optimization and artificial neural network. 2) By using the gray level co-occurrence matrix method, the texture features (correlation, angular second moment, contrast, etc.) will be extracted to retrieve wind direction. Further, the other texture features will be extracted in wind direction. The relationship between them and wind speed will be explored. A method based on multiple texture features will be established for sea surface wind retrieval. Additionally, the traditional local gradient method will be improved for efficiency and accuracy, and combined with the above method. This study is basic research. It will enrich the research on the relationship between polarimetric and texture features and sea surface wind field, and explore new ways for sea surface wind retrieval from SAR. It is novel and has important scientific significance.

随着高分辨率全极化合成孔径雷达（SAR）的发展，SAR能提供更多的极化和纹理信息供海面风场反演。但相应的海面风场反演研究却尚处起步阶段。本研究针对"如何利用极化和多种纹理特征来反演海面风场"这一问题进行探索，拟从以下两方面展开。1）在建立风浪全极化散射数值模型的基础上，分析极化参数与海面风场之间的关系。通过拟合模型－遗传优化和人工神经网络两种途径，探索全极化SAR地球物理模式函数的构建方法。2）采用灰度共生矩阵法，提取相关、角二阶矩及对比度等纹理特征以确定风向，在风向上进一步提取其它纹理特征，探索纹理特征与风速之间的关系，形成基于多种纹理特征的风场反演方法。另外,对传统局部梯度法进行改进，提高其效率和精度，并将其结合到上面方法中。本研究侧重基础性，将完善极化和纹理特征与海面风场之间关系的研究，并为SAR海面风场反演开拓新的思路，新颖且具有重要科学意义。

本项目开展了基于极化特征和纹理特征的全极化合成孔径雷达（Synthetic Aperture Radar，SAR）海面风场反演研究。本项目首先采用积分方程法结合海浪谱建立了风浪全极化散射数值模型，基于该模型研究了极化特征与海面风场之间的关系。本项目其次针对SAR海面风向反演给出了改进的梯度法。本项目最后提取了SAR图像的多种纹理特征，研究了纹理特征与海面风场之间的关系，并给出了基于纹理特征的SAR海面风向反演新方法。本项目的对比结果显示：相比传统的傅立叶变换法和梯度法，无论是采用了本项目中所给出的改进梯度法还是基于纹理特征的新方法，SAR所反演的海面风向和参考数据风向之间的差异均有所减小。本项目同时给出了基于纹理特征的海面风速反演新方法，该方法可作为SAR海面风速反演现有方法的一种补充。