Processing of high-frequency multibeam echo sounder data for seafloor characterization

Type Article
Date 2003
Language English
Author(s) Hellequin Laurent2, Boucher Jean-Marc2, Lurton Xavier1
Affiliation(s) 1 : IFREMER, TMSI AS, F-29280 Plouzane, France.
2 : ENST Bretagne, F-29285 Brest, France.
Source IEEE Journal of Oceanic Engineering (0364-9059) (IEEE), 2003 , Vol. 28 , N. 1 , P. 78-89
DOI 10.1109/JOE.2002.808205
WOS© Times Cited 111
Keyword(s) Seafloor classification, Multibeam echo sounder MBES, K distribution, Backscatter model
Abstract Processing simultaneous bathymetry and backscatter data, multibeam echosounders (MBESs) show promising abilities for remote seafloor characterization. High-frequency MBESs provide a good horizontal resolution, making it possible to distinguish fine details at. the water-seafloor interface. However, in order to accurately measure the seafloor influence on the backscattered energy,the recorded sonar data must first be processed and cleared of various artifacts. generated by the sonar system itself. Such a preprocessing correction procedure along with the assessment of its validity limits is presented here and applied to a 95-kHz MBES (Simrad EM1000) data set. Beam pattern effects, uneven array sensitivities, and inaccurate normalization of the ensonified area are removed to make possible further quantitative analysis-of the corrected backscatter images. Unlike low-frequency data where the average backscattered energy proves to be the only relevant feature for discriminating the nature of the seafloor, high-frequency MBES backscatter images exhibit visible texture patterns. This additional, information involves different statistical distributions of the backscattered amplitudes obtained from various seafloor types. Non-Rayleigh statistics such as K-distributions are shown to fit correctly the skewed distributions of experimental high-frequency data. Apart from the effect of the seafloor micro-roughness, a statistical model makes clear a correlation between the amplitude statistical distributions and the signal incidence angle made available by MBES bathymetric abilities. Moreover, the model enhances the effect of the first derivative of the seafloor backscattering strength upon statistical distributions near the nadir and at high incidence angles. The whole correction and analysis process is finally applied to a Simrad EM 1000 data set.
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