Sonar

Synthetic Aperture Sonar (SAS) provides the best opportunity for side-looking sonar mounted on underwater platforms to achieve high-resolution images. However, SAS processing requires strict constraints on resolvable platform motion. The most common approach to estimate this motion is to use the Redundant Phase Center (RPC) technique. Here the ping interval is set, such that a portion of the sonar array overlaps as the sensor moves forward. The time delay between the pings received on these overlapping elements is estimated using cross-correlation. These time delays are then used to infer the pingto-ping vehicle motion. Given the stochastic nature of the operational environment, some level of decorrelation between these two signals is likely.
In this research, two iterative signal decomposition methods well suited for nonlinear and non-stationary signals, are investigated for their potential to improve the Time Delay Estimation (TDE). The first of this type, the Empirical Mode Decomposition (EMD) was introduced by Huang in the seminal paper, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis and is the foundation for the algorithms used in this research. This method decomposes a signal into a finite sequence of simple components termed Intrinsic Mode Functions (IMFs). The Iterative Filter (IF) approach, developed by Lin, Wang and Zhou, builds on the EMD framework. The sonar signals considered in this research are complex baseband signals. Both the IF and EMD algorithms were designed to decompose real signals. However, the IF variant, the Multivariate Fast Iterative Filtering (MFIF) Algorithm, developed by Cicone, and the EMD variant, the Fast and Adaptive Multivariate Empirical Mode Decomposition (FAMVEMD) algorithm, developed by Thirumalaisamy and Ansell, preserve both the magnitude and phase in the decomposition and hence were chosen for this analysis.

Scour is the process of sediment erosion around bridge piers and abutments due to
natural and man-made hydraulic activities. Excessive scour is a critical problem that is
typically handled by enforcing design requirements that make the submerged structures
more resilient. The purpose of this research is to demonstrate the feasibilities of the Optical-
Based Green Laser Scanner and HydroLite Sonar in a laboratory setting to capture the 3D
profile of simulated local scour holes. The Green Laser had successfully reconstructed a
3D point-cloud imaging of scour profiles under both dry and clear water conditions. The
derived scour topography after applying water refraction correction was compared with the
simulated scour hole, and was within 1% of the design dimensions. The elevations at the
top and bottom surfaces of the 6.5-inch scour hole were -46.6 and -53.11 inches from the
reference line at the origin (0,0,0) of the laser scanner. The HydroLite Sonar recorded
hydrographical survey points of the scour’s interior surface. The survey points were then
processed using MATLAB to obtain a 3D mesh triangulation.

The problem of inverse scattering where the scattering structure is unknown, and the physical properties are predicted from the measured echo when the target is insonified with known waveforms, is investigated in this thesis. The scattering structure studied is a submerged, evacuated, spherical elastic shell. The formulation of the echo is carried out using thin shell theory for low and middle frequency range, which basically assumes that shear stresses are negligible. The echo is characterized by the form function in the frequency domain, and the impulse response in the time domain. The results of this thesis show that when using a chirp signal with a 200-250kHz bandwidth as the incident waveform, both the material and size of the shell can be recovered. However, the exact thickness of the shell wall couldn't be extracted.

This thesis describes an active sonar mounted to an Autonomous Underwater Vehicle (AUV) for measuring bubble clouds below breaking waves. A new development is the application of a very broadband sonar signal-processing scheme for the sonar. It is shown that using the active sonar on an Autonomous Underwater Vehicle provides reliable data and that good results are obtained by using a correlation processor. This thesis describes the optimum processing procedure for this application, resolution, and signal to noise constraints. Experimental results are given which show that bubbles can be imaged using an active sonar from an AUV platform. It was shown in the experimental results that the additive and the multiplicative processing produced good results for different situations. The multiplicative procedure was more consistent in the identification of bubble clouds than the additive process. One could see from the multiplicative images for the sea experiment where the bubble clouds were located while in the additive images one could only tell that a bubble cloud was identified.

The common approach for finding objects buried under the seabed is to use a single channel chirp reflection profiler. Reflection profiles lack information on target location, geometry and size. This thesis investigates methods for visualizing buried objects in noisy 3D acoustic data acquired by a small aperture scanning sonar. Various surface and volume rendering methods are tested with synthetic datasets containing fluid loaded spheres and with experimental data acquired with a 4-by-8 planar hydrophone array towed over buried objects with various aspects and size. The Maximum Intensity Projection is the best of the tested methods for real-time visualization of the data where a global overview of the targets is needed. A surface rendering technique such as the Marching Cubes is useful for offline measurement of the geometry and size of buried objects selected by the operator.

A new method is proposed to infer the geotechnical properties of the sea floor from its response to the frequency-modulated pulses emitted by the subbottom profiler called Chirp Sonar. The environment is assumed to be a multilayered medium, composed of homogeneous layers, or an inhomogeneous half-space with depth-dependent properties. The acoustic response of the sediment is computed using the Biot-Stoll theory. The Levenberg-Marquardt method is applied to fit the synthetic response to the experimental response of an homogeneous layer overlying the sea floor. The porosity, the permeability, the mean grain diameter, the mass density, the bulk modulus and the shear modulus within this sediment layer can be estimated. A multilayered medium with depth-dependent properties could be applied to this inversion technique in the future.

This thesis presents the development of a microprocessor based
navigational system. The integrated system is capable of determining
depth to the bottom, distance to the surface, and velocity
of a deep towed submersible. The system also alerts the user to
any reduction to forward safe distance limit. A discussion of
the hardware used to gather the data is presented. Software
development is discussed in great detail. The system utilizes
the Sixty Five Hundred microprocessor family. Advantages include
cost effectiveness and application versatility.

The purpose of the thesis is to investigate a multi-aspect reflection technique to generate 3D images of buried cylinders using the Buried Object Scanning Sonar (BOSS). Target imagery is constructed using a sequence of acoustic echoes generated as the sonar approaches and passes the buried target. However, for the sake of simplicity, the influence of the sediment on the scattering field will not be considered. This thesis investigates the multi-aspect technique by generating synthetic images of cylindrical targets to determine both the best method and the sonar parameters for reconstructing the shape of an elastic cylinder. Recommendations for deploying BOSS-252 and setting sonar parameters are provided based on quantitative measurements of the simulated images of cylindrical targets.

The Buried Object Scanning Sonar (BOSS) is being developed at Florida Atlantic University to image targets buried under the seabed. Tomographic images are constructed using a sequence of sonar transmissions while the vehicle is moving. This motion causes image distortion and should be measured and removed by mapping the echoes received to an absolute coordinate system. The aim of this thesis is to develop and simulate a technique for generating BOSS images that provide an accurate representation of target shape and size, by removing vehicle motion while mapping the image pixels. Synthetic acoustic data sets are generated by convolving the auto-correlated FM transmission pulse with the impulse response of an elastic sphere. Synthetic outputs of a Doppler velocity log and a 3-axis inertial measurement unit are generated to simulate vehicle motion. Noise is added to the sensor data to show the effects of motion sensor errors on image quality.

A numerical model that simulates the operation of a Forward Look Scan Sonar (FLSS) has been developed in this thesis. The model discretizes the sonar-projected signal by a set of rays using a geometrical approach. Bending of the rays due to varying acoustic wave speed is neglected. Simulated raw sonar data are generated, and used as input in the sonar processing algorithms to generate sonar images. Using the model, the influence of, the most critical characteristics of the sonar, including phase variations among the channels, non-homogeneous channel amplitude, and the number of bad channels, on the quality of the sonar image is determined. The results of the model are compared to real data from a low frequency FLS sonar (250 KHz) and a high frequency FLS sonar (600 KHz). There is good matching between the simulation and the operation of the two sonars and the performance was markedly enhanced by using the modeling results.