Abstract
Forward-looking sonar (FLS) underwater imaging systems are primarily used for measuring seafloor backscatter. These returns, however, may be occluded due to scattering from other objects in the water such as fish, bubbles, or other suspended objects, and in-band acoustic interference from sources like engines or other acoustic transmissions. The presence of non-seafloor scatterers or interference is most easily observed and estimated in the water column data, the portion of the time-series after the sonar has transmitted a ping, but before that ping has scattered off the seafloor and returned to the FLS. Analysis of the water column time-series returns can be leveraged to estimate the quality of seafloor imagery. In this study, we characterize bright scatterers that appear in the water column data using statistical tools and generate corresponding quality metrics to evaluate imagery.
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