Advisor

Martin Siderius

Date of Award

Fall 12-4-2017

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Electrical and Computer Engineering

Department

Electrical and Computer Engineering

Physical Description

1 online resource (viii, 81 pages)

Subjects

Ocean bottom -- Classification -- Remote sensing, Underwater acoustics

DOI

10.15760/etd.5944

Abstract

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.

Persistent Identifier

http://archives.pdx.edu/ds/psu/23377

Available for download on Tuesday, December 04, 2018

Share

COinS