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Rapid developments in the search for means to provide detailed seabed mapping has led to the introduction of the Bathymetric Side Scan Profiling Sonar (BSSPS) System, which uses a two-transducer interferometer to map seabed features. Error in the resolved relative phase of the BSSPS system has crippled its application for resolving very detailed seabed features. This present work is concerned with the study, analysis and evaluation of the sources contributing to the system relative-phase error. Most of the sources of noise contributing to the relative-phase error can be prevented or reduced by good instrumentation and careful design, except the glint and the newly introduced source of noise, sliding ladder (SL). These sources were found to be unavoidable and cannot be eliminated, being part of the backscattered signal. Glint is only influenced by the angle of incidence, y, transducer separation, d, and pulse duration t. Sliding ladder noise is influenced by the grazing angle, e, (angle of reception relative to the boresight), pulse duration, t, and transducer separation, d. Reducing t has the effect of slightly reducing the relative-phase error due to glint, but greatly increasing it due to SL. Alternatively, reducing d has the effect of reducing the error due to both glint and SL, but it degrades the system resolving power. The choice of d and t is decided by the type of application and required resolution. This work also develops the design and implementation of the inverse tan method used to separate the relative-phase and envelope of the two received signals. The inverse tan method for resolving the relative phase (complex signal processor) is found to be simple, easy to implement, and accurate. In order to study the contribution and effect of the individual sources of noise on the relative-phase error, the BSSPS system was simulated. The designed computer model proved to be flexible, reliable and very useful. It was extensively used to test theoretical analysis as well as to achieve individual and collective glint and SL effects. Also the system was employed to test the influence of some of the system parameters on the sources of noise. Using the BSSPS simulated system we were able to provide some valuable guidelines for the sonar design and application concerning resolution, optimum mapped distance and an approach to reduce the relative-phase error (averaging). Applications of the present findings are not restricted to sonar systems, but would be just as useful to similar radar applications.

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This dissertation explores the problems raised by the design and construction of a real-time sonar interpreter operating in a three dimensional marine context, and then focusses on two major research issues inherent in sonar interpretation: the treatment of observer and object motion, and the efficient exploitation of the specularity of acoustic reflection. The theoretical results derived in these areas have been tested where appropriate by computer simulation. In the context of mobile marine robotics, the registration of sensory data obtained from differing viewpoints is of paramount importance. Small marine vehicles of the type considered here do not carry sophisticated navigational equipment, and cannot be held stationary in the water for any length of time. The viewpoint registration problem is defined and analysed in terms of the new problem of motion resolution: the task of resolving the apparent motion of objects into that part due to the movement of the observer and that due to the objects' proper motion. Two solutions to this under constrained problem are presented. The first presupposes that the observer orientation is known ~ priori so that only the translational observer motion must be determined. It is applicable to two and three-dimensional situations. The second solution determines both the translational and the rotational motion of the observer, but is restricted to a two-dimensional situation. Both solutions are based on target extensively tested in two tracking techniques, and have dimensions by computer simulation. been The necessary extensions to deal with full three-dimensional motion are also discussed. The second major research issue addressed in this thesis is the efficient use of specularity. Specular echoes have a high intrinsic information content because of the alignment conditions necessary for their generation. In the marine acoustic context they provide a significant proportion of the information available from an acoustic ranger. I suggest a new method that uses directly the information present in specular reflections and the history of the vehicle motion to classify the specular echo sources and infer the local structure of the objects bearing them. The method builds on the output of a motion resolution system. Six distinct types of specular echo source are described and three properties useful for their discrimination are discussed. A suitable inference system for the analysis and classification of specular echo sources is also proposed.

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This thesis presents the development of a computer model for the simulation of the sidescan sonar process. The motivation for the development of this model is the creation of a unique and powerful visualisation tool to improve understanding and interpretation of the sidescan sonar process and the images created by it. Existing models tend to generate graphical or numerical results, but this model produces synthetic sidescan sonar images as the output. This permits the direct visualisation of the influence of individual parameters and features of the sonar process on the sidescan images. The model considers the main deterministic aspects of the underlying physical processes which result in the generation of sidescan sonar images. These include the propagation of the transmitted pulse of acoustic energy through the water column to its subsequent interaction and scattering from the rough seafloor. The directivity and motion characteristics of the sonar transducer are also incorporated. The thesis documents the development of the model to include each of these phenomena and their subsequent effect on the sidescan sonar images. Finally, techniques are presented for the investigation and verification of the synthetic sidescan images produced by the model.

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This thesis considers the use of multivariate statistical methods in relation to a common signal processing problem, that of detecting features in sound recordings which contain interference, distortion and background noise. Two separate but related areas of study are undertaken, first, the compression and noise reduction of sounds; second, the detection of intermittent departures ('signals') from the background sound environment ('noise'), where the latter may be evolving and changing over time. Compression and noise reduction are two closely related areas that have been studied for a wide range of signals, both one dimensional (such as sound) and two dimensional (such as images). Many well known techniques used in this field are based on the Fourier transform. In this work, we show how the comparative recent wavelet transform is superior for sound data involving short duration signals (such as shrimp clicks) whilst being at least as good as the Fourier transform for longer duration signals (such as dolphin whistles). Various noise reduction techniques involving thresholding wavelet transforms are examined and compared. We show how none of the standard threshold methods cope well with underwater sounds to any reasonable degree and propose a new technique, known as RunsThresh to overcome the perceived problems. The performance of this new method is contrasted with that of various standard thresholds. Signal identification for underwater sounds is an area that has been examined in detail in much previous work. Here, we build upon the results gleaned from noise reduction to develop a methodology for detecting signals. The underwater noise environment is dynamically modelled using recursive density estimation of certain summary features of its wavelet decomposition. Observations which are considered to be outliers from this distribution are flagged as 'signal'. The performance of our signal detection method is illustrated on artificial data, containing known signals, and on real data. This performance is compared with standard Fourier based methods for both cases. Finally in this thesis, several ideas are presented and discussed which consider how the noise reduction and signal detection techniques examined in earlier chapters could be developed further, for example, in order to classify detected signals into different classes. These ideas are presented in outline only and are not followed up in detail, since they represent interesting directions for future study, rather than a primary focus of this thesis.