Abstract: The present invention relates to a novel system for seafloor classification using artificial neural network (ANN) hybrid layout with the use of unprocessed multi-beam backscatter data and more importantly, this invention relates to an real-time seafloor roughness classifier using backscatter data after training the self-organized mapping (SOM) network and learning vector quantization (LVQ) network wherein, the system of the present invention has the unique capability for the combined use of unsupervised SOM followed by supervised LVQ to achieve a highly improved performance in the said roughness classification, which was hitherto non-existent and has the additional capability for the use of a combination of the two variants of the LVQ layout to work together to achieve the best results in seafloor roughness classification.

Abstract: The present invention relates to a novel system for seafloor classification using artificial neural network (ANN) hybrid layout with the use of unprocessed multi-beam backscatter data and more importantly, this invention relates to an real-time seafloor roughness classifier using backscatter data after training the self-organized mapping (SOM) network and learning vector quantization (LVQ) network wherein, the system of the present invention has the unique capability for the combined use of unsupervised SOM followed by supervised LVQ to achieve a highly improved performance in the said roughness classification, which was hitherto non-existent and has the additional capability for the use of a combination of the two variants of the LVQ layout to work together to achieve the best results in seafloor roughness classification.

Abstract: The present invention provides a method for determining sea floor roughness using multibeam echosounder, said method comprising providing backscatter, bathymetry and multibeam operational parameters; removing system gain from the backscatter data to obtain real seafloor backscatter data; calculating across track seafloor slope; incorporating correction factor in actual beam arrival angles; calculating seafloor area; measuring backscatter strength; obtaining backscatter strength data at 1° angle; obtaining power law parameters; using the above-obtained parameters in a seafloor roughness power law model; splicing the multibeam backscatter data; including sediment volume roughness model; and verifying the validity of the composite roughness model.

Abstract: The present invention provides a method for determining sea floor roughness using multibeam echosounder, said method comprising providing backscatter, bathymetry and multibeam operational parameters; removing system gain from the backscatter data to obtain real seafloor backscatter data; calculating across track seafloor slope; incorporating correction factor in actual beam arrival angles; calculating seafloor area; measuring backscatter strength; obtaining backscatter strength data at 1° angle; obtaining power law parameters; using the above-obtained parameters in a seafloor roughness power law model; splicing the multibeam backscatter data; including sediment volume roughness model; and verifying the validity of the composite roughness model.