Current commercial solutions for processing acoustic data with the aim of seafloor characterization does not take full advantage of the wide spectra of information collected by modern sonars (e.g., water column data, multiple sectors). In addition, those solutions tend to act as a ‘magic black-box’ with only a few user-defined parameters. This can be seen as an advantage (it makes these technologies available to a large community), but it also engenders a lack of data reproducibility. Currently, it is a real challenge to ‘properly’ merge backscatter-based products from different vendors (and even from the same vendor given the lack of metadata).
In order to mitigate both issues, we are developing a different approach. The proposed workflow is organized into two main phases: the first part focuses on artifact identification and reduction, while the second part is product-oriented. The artifact-oriented phase applies a (growing) set of algorithms to facilitate the identification of corrupted data so that they can then be ignored or, if required by the user, reconstructed using several different techniques. This approach also provides a metric that can then be used to identify which ping should be excluded during seafloor characterization.