机载SAR探测图像中归一化雷达截面随入射角变化规律应用

机载SAR对海探测时,探测范围小和时空匹配难等局限使其无法借助风条纹和辅助资料反演海面风矢量.本文在仿真研究CMOD5.N地球物理模型参数的函数关系,实例分析机载SAR探测图像中距离向均值曲线变化规律的基础上,发现相同风向、风速条件下,CMOD5.N模型构建的标准曲线和探测图像的距离向均值曲线遵循统一的归一化雷达截面随入射角变化规律,且两者具有良好的相关性.据此,本文提出将距离向均值曲线与标准曲线逐条匹配,采用相关系数判定两者的相关程度,选择使得相关系数绝对值最大的标准曲线作为最优匹配曲线,进而直接确定风向和风速的海面风矢量反演方法.机载SAR飞行探测实验结果表明,海面风矢量反演结果与浮标观测结果的均方根误差为风向11.3°,风速0.9m·s-1,高于反演精度指标要求,原因在于该方法既避免了机载SAR探测图像中斑点噪声的影响,又不会产生局部最优解,提高了海面风矢量反演精度.

Application research for change rule of normalized radar cross section changes with incidence angle in airborne SAR sounding image

Based on high mobility, airborne SAR can be used as an effective means of ocean surface wind field fine sounding near coast, which makes up the lack of timely sounding from spaceborne SAR. Because of the limitation of small sounding range and difficult temporal and spatial matching, airborne SAR can't use wind streaks and auxiliary information to retrieve ocean surface wind vector. It's an important issue for ocean surface wind vector retrieval from airborne SAR, which gets rid of wind streaks and auxiliary information, and directly retrieves wind vector from sounding image.Based on simulation research function relationship of CMOD5.N geophysical model parameter and instance analysis change rule of airborne SAR sounding image's distance to the mean curve, we discover that standard curve built by CMOD5.N model and distance to the mean curve of sounding image follow an uniform change rule of normalized radar cross section changes with incidence angle in the same wind direction and speed condition, and both have good correlation. Accordingly, we present an ocean surface wind vector retrieval method. We match distance to the mean curve and standard curve one by one, and use correlation coefficient to determine correlation between the two, and select the standard curve when correlation coefficient absolute value is maximum value as the optimal matching curve, finally directly determine wind direction and wind speed.Airborne SAR flight sounding experimental results show that root mean square errors between sounding data retrieval results and buoy observations are wind direction 11.2° and wind speed 0.8 m·s^-1, wind direction 10.6° and wind speed 0.8 m·s^-1, wind direction 12.0° and wind speed 1.1 m·s^-1 on July 26, July 30 and August 5, respectively. The total root mean square error between ocean surface wind vector retrieval results and buoy observations is wind direction 11.3° and wind speed 0.9 m·s^-1. Retrieval results are better than wind direction 20° and wind speed 2 m·s^-1, and better than retrieval accuracy indicator. Because retrieval method avoids the effect of speckle noise in airborne SAR sounding image, and does not produce local optimal solution, finally improves ocean surface wind vector retrieval accuracy. The polarization correlation coefficient can be used to judge wind direction trend, but there is a small number of misjudgment. The reason is that sounding data differences between airborne SAR and RADARSAT-2 SAR in sounding width and platform stability, which cause differences in the variation of polarization correlation coefficient with respect to wind direction.These research results can be used in ocean surface wind vector operational sounding of airborne SAR. Because of experimental condition restriction, this article only carried out sounding experimentunder moderate sea conditions. We will carry out more experimental research, especially in high wind speed conditions, and further validate and improve retrieval method. In addition, we will carry out systematic research of polarization scattering characteristics from airborne fully polarimetric SAR, and explore effective ways to remove wind direction ambiguity.