基于RADARSAT-2雷达数据的海面风速反演方法研究

发布时间：2018-07-23 16:08

【摘要】：随着社会对传统能源消耗的增多,太阳能、风能等可再生资源具有巨大的应用前景,我国海上风能资源十分丰富,将成为我国资源转型的重要方向之一。利用合成孔径雷达是目前获取高空间分辨率海面风场数据的常用方法之一,根据雷达接收到的后向散射系数同海面风矢量的关系,快速获取海面风场数据,可以为近海风能资源的开发和利用提供高空间分辨率的海面风场基础数据。本文基于高空间分辨率的合成孔径雷达反演海面风场原理,采用C波段海面后向散射系数(NRCS)与风矢量经验关系构建的地球物理模式函数(GMF)和C波段交叉极化海面散射模型(C-2PO),利用具有多极化方式、多种成像模式和高空间分辨率等特点的RADARSAT-2卫星数据12景,以我国东部海域为研究区进行海面风速反演。本文首先选用NOAA提供的浮标实测数据对ERA-Interim(Interim Reanalysis)再分析风场数据进行验证分析,结果表明,ERA-Interim数据风速和风向的均方根误差分别为0.98m/s和12.79°,与浮标实测数据拟合度较好,表现出较高的精度,判定为可信数据,因而选用ERA-Interim风场数据作为RADARSAT-2雷达数据反演海面风速的初始风向数据和风速验证数据。RADARSAT-2雷达数据具有多极化方式的特点,在本文中,根据不同极化方式的雷达数据采用相应的模型进行海面风速反演。对于RADARSAT-2的VV极化数据分别采用三种主流的C波段地球物理模式函数(CMOD4、CMOD5和CMOD-IRF2)进行海面风速反演,结果表明,VV极化数据采用CMOD4模型反演的风速精度最高,均方根误差为1.27m/s,可用于RADARSAT-2数据进行海面风速反演；对于HH极化数据,在对比分析三种常用的极化比模型(Bragg模型、Thompson模型和Kirchhoff模型)的基础上,再分别采用三种GMF模型进行风速反演,结果表明,采用Kirchhoff极化比模型时更适用于RADARSAT-2HH极化数据的海面风速反演,而三种GMF模型反演风速效果差异不大,均方根误差在2m/s以内；对于VH和HV极化数据,本文选用精细全极化模式数据进行研究,采用C波段交叉极化海面风速反演模型(C-2PO模型)进行海面风速反演,同时利用GMF模型对相应的VV和HH极化数据进行海面风速反演,并将结果与ERA-Interim数据进行对比分析。研究结果表明,VH和HV极化数据反演精度基本相同,均可以反演出较高精度的海面风速,平均偏差在±1m/s左右,均方根误差在1.5m/s以内,并且反演效果要优于同极化数据。同时,ScanSAR模式交叉极化数据的后向散射系数同样随海面风速的增大而增大,并表现出一定的线性关系。综合RADARSAT-2数据的海面风速反演结果可以看出,同极化和交叉极化数据均可以得到较高精度的海面风速,其中精细全极化模式的VH和HV极化数据可以在不需要外部风向数据情况下直接利用C-2PO模型进行海面风速反演,并且其反演结果要更优于利用GMF模型的VV和HH极化数据。全极化模式交叉极化数据在海面风速反演上表现出比传统方法较为显著的优势,将成为未来海面风速反演的发展方向。
[Abstract]:With the increasing consumption of traditional energy in society, the renewable resources such as solar energy and wind energy have great application prospects. The offshore wind energy resources in China are very rich and will become one of the important directions in the transformation of resources in China. The relationship between the backscattering coefficient and the wind vector of the sea surface wind vector is obtained, and the data of the sea surface wind field can be obtained quickly. It can provide the high spatial resolution of the sea surface wind field data for the exploitation and utilization of the offshore wind energy resources. This paper uses the principle of the sea surface wind field inversion based on the high spatial resolution synthetic aperture radar, and uses the C band backscatter system. The geophysical model function (GMF) and the C band cross polarization sea surface scattering model (C-2PO) are constructed by the empirical relationship between NRCS and the wind vector. The 12 views of RADARSAT-2 satellite data, which are characterized by multi polarization, multiple imaging modes and high spatial resolution, are used to invert the sea surface wind velocity in the eastern area of China. Using the measured data of buoy provided by NOAA to verify and analyze the data of ERA-Interim (Interim Reanalysis) reanalysis of wind field, the results show that the root mean square error of wind speed and wind direction of ERA-Interim data is 0.98m/s and 12.79 degrees respectively, and the fitting degree is better with the measured data of buoys, which shows high accuracy and is determined as credible data, so ERA-I is selected. Nterim wind field data is used as RADARSAT-2 radar data to inverse the initial wind direction data of sea surface wind speed and wind speed verification data,.RADARSAT-2 radar data have the characteristics of multi polarization. In this paper, the corresponding model is used to inverse the sea surface wind velocity according to the radar data of different polarization modes. For the VV polarization data of RADARSAT-2, respectively. Three main mainstream C band geophysical model functions (CMOD4, CMOD5 and CMOD-IRF2) are used to retrieve the sea surface wind speed. The results show that the velocity accuracy of the VV polarization data is the highest with the CMOD4 model, and the mean square root error is 1.27m/s, which can be used for the inversion of the wind velocity of the RADARSAT-2 data. For the HH polarization data, three kinds of normal data are compared and analyzed. On the basis of the polarization ratio model (Bragg model, Thompson model and Kirchhoff model), three GMF models are used for wind velocity inversion respectively. The results show that the use of the Kirchhoff polarization ratio model is more suitable for the inversion of the sea surface wind velocity of the RADARSAT-2HH polarization data, while the three kinds of GMF models have little difference in wind speed and the root mean square error. Within 2m/s, for VH and HV polarization data, this paper uses fine full polarimetric data to study, uses the C band cross polarization sea surface wind velocity inversion model (C-2PO model) to retrieve the sea surface wind speed, and uses GMF model to inverse the corresponding sea surface wind velocity of the corresponding VV and HH polarization data, and carries out the results with the ERA-Interim data. The results show that the inversion accuracy of VH and HV polarization data is basically the same, all of which can reverse the high precision of the sea surface wind speed, the average deviation is about 1m/s, the mean square root error is within 1.5m/s, and the inversion effect is better than the same polarization data. At the same time, the backscattering coefficient of the ScanSAR mode cross polarization data is also with the sea surface wind. The results of the sea surface wind velocity inversion of the integrated RADARSAT-2 data show that both the same polarization and cross polarization data can obtain higher precision of the sea surface wind speed, in which the VH and HV polarization data of the fine and full polarization mode can be used directly by C- without the need of external wind direction data. The 2PO model performs sea surface wind velocity inversion, and its inversion results are better than the VV and HH polarizing data using the GMF model. The fully polarized cross polarization data shows a more significant advantage over the sea surface wind velocity inversion, and will be the direction of the future sea surface wind velocity inversion.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：P714.2;P715.7

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