From 10 m to 11000 m, Automatic Processing Multi-Beam Bathymetric Data Based on PGO Method

Multi-beam echo sounders (MBESs) are characterized by the high resolution and density of sounding data. The processing MBES bathymetry data is special interest currently in marine surveying. Combined Uncertainty Bathymetry Estimator (CUBE) surface filtering main MBES-processing algorithms for outliers. These involve five adjustable parameters; however, few studies have looked at parameter optimization. In this paper, a Parameter Group Optimization (PGO) method that determines optimal parameters CUBE based on seafloor topographic characteristics survey area presented. includes typical selection, grid analysis, group testing batch processing, analysis. Raw datasets from shallow- deep-water areas (between 10 11000 m deep) used to validate proposed method. results show when optimized algorithm, outliers automatically eliminated; processed good agreement with derived traditional manual method, while efficiency can be improved more than 8 times.