Three-Dimensional Modeling of Seafloor Backscatter from Sidescan Sonar for Autonomous Classification and Navigation

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Abstract
Sonars will continue to play an important role in world-modeling for autonomous underwater systems because of the greater range available to acoustic sensors compared with other sensing modalities. However, attempts to automate the interpretation of sidescan sonar data are typically based on two-dimensional image-processing and pattern-analysis techniques. Such sidescan "images" provide only indirect, qualitative, and view-dependent information, since the intensity of the returned signal is a function of both seafloor shape and scattering properties of the bottom materials. This overview of work in progress at the Deep Submergence Laboratory describes several techniques for three-dimensional sonar processing in which seafloor shape information is used to reduce geometric and radiometric dependencies in the intensity signal. The approach is developed using Sea Beam bathymetry and Sea MARC I sidescan data. Preliminary results are also described for new split beam sidescan sonars designed for high-resolution seafloor characterization. Complex-domain processing of the quadrature-sampled signal gives amplitude and phase for three-dimensional modeling, and offers a measure of signal coherence and modeling certainty. The processed output is a quantitative model of three-dimensional shape and backscatter characteristics that will be applied to feature classification and terrain-relative navigation for intelligent underwater vehicles.

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