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

Abstract

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.