Localization is a classic and complex problem in the field of mobile robotics. It becomes particularly challenging in an aqueous environment because currents within the water can move the robot. A novel localization module and corresponding localization algorithm for experimental autonomous underwater vehicles is presented. Unlike other available positioning systems which require fixed hardware beacons, this custom built module relies only on information available from sensors on-board the vehicle and knowledge of its bounded domain. This allows the user to save valuable time which would otherwise be devoted to the setup and calibration of a beacon or sensor network. The module uses three orthogonal ultrasonic transducers to measure distances to the tank boundaries. Using the measured tri-axial orientation of the vehicle, the algorithm analytically determines the robot's position within the domain in absolute coordinates. Certain vehicle states do not allow the position to be completely resolved by the algorithm alone. In this case, state estimation is used to estimate the robot position until its state is no longer indeterminate. The modular design of this system makes it ideal for application on underwater vehicles which operate in a bounded environment for research purposes. An experimental version of the module was constructed and tested in the WPI swimming pool and showed successful localization under normal conditions.

Beamforming is a signal processing technique used in sensor arrays to direct signal transmission or reception. Beamformer combines input signals in the array to achieve constructive interference at particular angles (beams) and destructive interference for other angles. According to the following facts: 1- Beamforming can be computationally intensive, so real-time sonar beamforming algorithms in sonar devices is important. 2- Parallel computing has become a critical component of computing technology of the 1990s, and it is likely to have as much impact over the next 20 years as microprocessors have had over the past 20 [5]. 3- The high-performance computing community has been developing parallel programs for decades. These programs run on large scale, expensive computers. Only a few elite applications can justify the use of these expensive computers [2]. 4- GPU computing has the ability of parallel computing and it could be available on the personal computers. The objective of this thesis is to use Graphics Processing Unit (GPU) as real-time digital beamformer to accelerate the intensive signal processing.

This thesis presents methods for improving the detection processing of active sonar systems. Measures to compensate for or even exploit particular characteristics of the detection problem for these systems are considered. Reverberation is the result of scattering of the transmitted signal from non-target features. Multipath and variability are particularly pronounced for underwater sound signals because propagation is very sensitive to spatial and temporal temperature variations. Another problem is the low pulse repetition rate due to the relatively low speed of sound. This low data rate reduces tracking and detection performance. / Reverberation often arises as the sum of many small contributions so that received data has a multivariate Gaussian distribution. Estimating the large numbers of parameters in the distribution requires a lot of data. This data is not available because of the low data rate. Representing the scattering as an autoregressive process reduced the data requirement but at some cost to modelling accuracy. A coupled estimator algorithm is developed to estimate the parameters. Detection performance is compared to other models and estimators that assume Gaussian statistics. / To counter multipath distortion the delays and strength of the paths are estimated using a version of the expectation maximisation (EM) algorithm. The magnitude of path amplitudes is then used to decide if a target is present. The EM algorithm is also suggested as a way to find the likely amplitude of reverberation from a few large scatterers that that form non-Gaussian reverberation. / Non-parametric methods are considered for detection of short duration incoherent signals in a duct. These detectors compare the ranks of the data in a region being tested for target present to another region assumed to have no target. Simulations are used to explore performance and what happens when the independent samples assumption is violated by the presence of reverberation. / More data can improve detection. Exploiting data from multiple transmissions is difficult because the slow speed of sound allows targets to move out of detection cells between transmissions. Tracking the movements of potential targets can counter this problem. The usefulness of Integrated Probabalistic Data Association (IPDA), which calculates a probability of true track as well as track properties, is considered as a detection algorithm. Improvements when multiple receivers are used as well as limitations when sensor positions are uncertain are investigated.

Thesis (Ph.D.)--University of Wollongong, 2003. / Typescript. Bibliographical references: leaf 461-470.