从SAR子孔径序列图像中提取海洋动态特征的改进相位相关法(英文)

An Improved Phase Correlation Method for Obtaining Dynamic Feature of the Ocean from Sequential SAR Sub-aperture Images

动态特征是海洋信息中的重要方面。但是在通常的SAR图像处理中动态信息往往会被丢失,因为这些方法大多把SAR图像看成是观测区域的瞬时状态。实际上,我们可以从SAR子孔径序列图像中获取动态信息,因为我们知道SAR不同方位向孔径对应不同的成像瞬间。从序列图像中获取动态信息的一个关键步骤就是图像匹配。但是SAR子孔径图像的强噪声特性使得传统的图像匹配算法难以奏效。该文中,为了应对SAR子孔径图像中的噪声问题,我们提出了一种改进的相位相关法。仿真实验表明改进的算法在多数情况下都可以达到0.15像素以上的精度以及很好的噪声鲁棒性。分析表明,该方法可以适用于从中等分辨的机载SAR图像和高分辨的星载SAR图像中提取动态特征,速度提取精度可以达到0.15-0.3 m/s。该文将该方法用于一个实际的机载SAR图像的处理,反演的海面动态速度在0.05-0.5 m/s左右,这个速度范围符合海面上一般的流速范围。

Dynamic features are important aspects of the ocean. However the dynamic information is lost in most conventional Synthetic Aperture Radar （SAR） image processing methods, because they treat the image as an instantaneous state of the observed area. In fact, we can obtain dynamic features of the ocean from sequential sub-aperture images, because we know that the different parts of the azimuthal aperture correspond to different imaging instances. A key step for retrieving the dynamic features from sequential images is image-matching. However, the heavy noise characteristic of sub-aperture SAR images renders the traditional image-matching methods ineffective. In this paper we propose an image matching method based on improved phase correlation to deal with the heavy noise problem of SAR sub-aperture images. Experimental results show that the improved image-matching method presents an accuracy of 0.15 pixel and noise robustness. The analysis indicates that the improved algorithm is competent for obtaining dynamic information from the medium resolution airborne SAR images or high resolution spaceborne SAR images with 0.15-0.3 m/s estimation precision under most SNR conditions. The improved algorithm was used on an airborne SAR data to retrieve the movement velocity. The retrieved velocity ranged from 0.05-0.5 m/s, which seems to be reasonable value for the ocean current velocity.