合成孔径雷达提取海面风、浪参数的研究

发布时间：2017-12-30 22:32

本文关键词：合成孔径雷达提取海面风、浪参数的研究　出处：《浙江海洋大学》2017年硕士论文　论文类型：学位论文

【摘要】：合成孔径雷达(Synthetic Aperture Radar,SAR)是一种主动式微波成像雷达,其工作不受外在天气状况影响,具有全天候、全天时、高分辨率的海洋遥感观测能力。利用SAR来开展对海洋的研究已成为一个有效便捷的手段,其高分辨率的SAR图像在海面风场和海浪参数的反演方面研究具有重大意义。在前人的研究基础上,本文对SAR图像反演海面风场和海浪参数开展了相关研究。用于X波段SAR图像海面风场反演的地球物理模型函数(GMF)XMOD1,XMOD2和SIRX-MOD都是基于VV极化发展而来的。目前,仅包含了雷达入射角的极化率模型XPR结合X波段的GMF已经被用于HH极化TerraSAR-X图像海面风场的反演。而之前的双极化TerraSAR-X图像反演海面风场的研究中发现极化率模型与海面风速存在一种特别的关系。因此,为了提高HH极化TerraSAR-X图像海面风场反演的精度,本文引入了一个同时包含雷达入射角和海面风速的极化率模型,本文称之为XPR2。通过56幅双极化TS-X和TD-X图像以及与之匹配的ECMWF风场数据拟合出XPR2。再利用38幅HH极化TerraSAR-X图像和与之对应的浮标测量值验证XPR2的有效性。验证的结果显示,采用XPR2反演结果的均方根误差为1.79m/s,偏差为0.68m/s,优于XPR反演结果的均方根误差为2.31m/s,偏差为0.93m/s,另外,本文基于波段极化的Sentinel-1的SAR图像,提出了一个反演有效波高H_s和平均波周期的半经验算法。半经验算法描述的是H_s与截断波长、雷达入射角和波浪传播方向与雷达距离向之间的夹角的经验关系。此外,T_(mw)可以通过另一个H_s与截断波长的经验关系计算得到。我们收集了106幅波段极化Sentinel-1 SAR图像和与之匹配的浮标实测数据,并从106幅SAR图像中一共采集到幅与浮标对应的子图像,用其中93幅子图像用来拟合半经验算法中的系数,剩下的57幅子图像用来验证半经验算法。比较结果显示H_s的RMSE为0.69m,SI为18.3%,Bias为0.11m;T_(mw)的RMSE为1.86s,SI为24.8%,Bias为0.62s。结果表明本文的H_s半经验算法适合Sentinel-1的SAR图像海浪参数的反演。
[Abstract]:Synthetic Aperture radar (SAR) is an active microwave imaging radar. High-resolution ocean remote sensing observation capability. Using SAR to carry out ocean research has become an effective and convenient means. The high resolution SAR images are of great significance in the retrieval of sea surface wind field and ocean wave parameters. In this paper, we have carried out a relative study on the inversion of sea surface wind field and sea wave parameters by SAR image. The geophysical model function for the inversion of sea surface wind field in X-band SAR image is GMF / XMOD1. Both XMOD2 and SIRX-MOD are based on VV polarization. The polarizability model (XPR), which only includes the radar incident angle, combined with X-band GMF, has been used to retrieve the sea surface wind field in the HH-polarized TerraSAR-X image. The previous dual-polarization TerraSA has been used to retrieve the sea surface wind field. It is found that there is a special relationship between the polarizability model and the wind speed of the sea surface in the study of R-X image inversion of the sea surface wind field. In order to improve the accuracy of sea surface wind field inversion in HH polarimetric TerraSAR-X images, a polarizability model including both radar incidence angle and sea surface wind speed is introduced in this paper. In this paper, XPR2 is called XPR2.The XPR2 is fitted by 56 bipolar TS-X and TD-X images and corresponding ECMWF wind field data. 38 HH polarimetric TerraSA images are used to fit XPR2. R-X images and corresponding buoy measurements verify the validity of XPR2. The root mean square error (RMS) of XPR2 inversion is 1.79 m / s and the deviation is 0.68 m / s, which is better than that of XPR inversion (2.31 m / s). The deviation is 0.93 m / s, in addition, the SAR image based on the band polarization of Sentinel-1 is presented in this paper. A semi-empirical algorithm for inversion of effective wave heights and mean wave periods is proposed. The semi-empirical algorithm describes HSCs and truncated wavelengths. The empirical relationship between the angle of incidence and the direction of wave propagation and the direction of radar range. Till. We have collected 106 polarimetric Sentinel-1 SAR images and the corresponding buoy measured data. The sub-images corresponding to the buoy are collected from 106 SAR images, and 93 sub-images are used to fit the coefficients in the semi-empirical algorithm. The remaining 57 sub-images are used to verify the semi-empirical algorithm. The comparison results show that the RMSE of HSCs is 0.69 mSI is 18.3mBias is 0.11m. The RMSE of T _ 2M _ w is 1.86s / m ~ (-1) and the SI is 24.8%. The Bias is 0.62s. The results show that the Hs semi-empirical algorithm proposed in this paper is suitable for the inversion of wave parameters in SAR images of Sentinel-1.
【学位授予单位】：浙江海洋大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P715

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