The sub-bottom profiler is a valuable tool for obtaining high-resolution shallow stratigraphic data in marine geological and geophysical surveys. To detect and acquire the structural characteristics of small submarine objects, we developed a data processing method that utilizes 2D data to construct a 3D structural model. We conducted application experiments using sub-bottom profile detection data from Chuanshan Islands, which were explored using China’s most advanced unmanned exploration platform and commercial shallow formation profiling system. To create high-resolution 3D seafloor structure models from recorded 2D sub-bottom profile datasets, an optimized data processing sequence was devised, comprising two stages: 2D data processing and 3D data processing. The 2D data processing stage involved spectrum analysis, band-pass filtering, matching filtering, time-varying gain, and surge correction. The subsequent 3D data processing stage encompassed ping location reallocation, static correction, and extraction of feature layer information. Notably, the final pseudo-3D sub-bottom profile time slice exhibited significant amplitude variations near the target body. This methodology represents an extension of the application of 2D sub-bottom profile data, enhancing the target recognition capabilities of such data. To further improve the precision of target body characterization, we used ArcScene 10.0 to create a 3D sub-bottom profile formation model spatial database. We constructed a submarine 3D formation structure model to show the 3D structural characteristics of the target body in detail and identified a seabed target body measuring 6.4 X 9.2 X 10 m.
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