Physics Based Approach for Seafloor Classification

The seafloor properties are of high importance for many applications such as marine biology, oil and gas exploration, laying cables, dredging operations and off-shore construction. Several approaches exist to classify the properties of the seabed. These include taking direct samples of the seabed (e.g., coring), however, these methods are costly and slow. Underwater acoustic remote sensing techniques are of interest because they are lower cost and faster. The information about the seabed properties can be extracted by studying the energy of single beam echo sounders (SBES). This can be done by either phenomenological or numerical methods [1], [2]. This research investigates a numerical, model-data fitting method using a high frequency backscattering model developed by Jackson et al [3]. In this inversion modeling method, the matching process between the model and average echo envelope provides information about the sediment parameters, namely the sediment mean grain size (Mz) as the indicator of the seabed type, spectral parameter (W2) as the indicator of seabed roughness and normalized sediment volume parameter σ2 as the indicator of the scattering due to sediment inhomogeneities