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EMPIRIC AND DYNAMIC DETECTION OF THE SEA BOTTOM TOPOGRAPHY FROM SYNTHETIC APERTURE RADAR IMAGE

机译:从合成孔径雷达图像经验和动态检测海底地形

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摘要

In this study, we develop empiric and dynamic methods to detect the underlying sea bottom topography from synthetic aperture radar (SAR) images. The ocean bottom features can be seen from SAR images due to the modulation of the surface waves by the nonuniform currents, which, by motion equations, should be a function of depth. We first derive the SAR image equation at a given time from Valenzuela's formula and the expression of micro-scale wave spectrum. By integrating the SAR image equation and the governing equations for ocean currents, we establish the "forward and inverse problems" for dynamic detection of topography. To utilize the SAR images, we separate the current modulation scale from the surface waves by a two-dimensional empirical mode decomposition method based on the Delaunay triangulation with the most protruding principle and the Berstein-Bezier fitting and interpolation with the most optimum principle. Examples of bottom topography detection from SAR images are presented..
机译:在这项研究中,我们开发了经验和动态方法来从合成孔径雷达(SAR)图像中检测潜在的海底地形。由于非均匀电流对表面波的调制,从SAR图像中可以看到海底特征,通过运动方程,这应该是深度的函数。我们首先从Valenzuela公式和微尺度波谱的表达式推导给定时间的SAR图像方程。通过整合SAR图像方程和洋流控制方程,我们建立了用于地形动态检测的“正反问题”。为了利用SAR图像,我们采用二维经验模式分解方法将电流调制比例从表面波中分离出来,该方法基于具有最突出原理的Delaunay三角剖分和具有最优化原理的Berstein-Bezier拟合和内插。给出了从SAR图像检测底部地形的示例。

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