Mill, Robert William (2008) The application of auditory signal processing principles to the detection, tracking and association of tonal components in sonar. PhD thesis, University of Sheffield.
Abstract
A steady signal exerts two complementary effects on a noisy acoustic environment:
one is to add energy, the other is to create order. The ear has evolved mechanisms to
detect both effects and encodes the fine temporal detail of a stimulus in sequences of
auditory nerve discharges. Taking inspiration from these ideas, this thesis investigates
the use of regular timing for sonar signal detection. Algorithms that operate on the
temporal structure of a received signal are developed for the detection of merchant
vessels. These ideas are explored by reappraising three areas traditionally associated
with power-based detection.
First of all, a time-frequency display based on timing instead of power is developed.
Rather than inquiring of the display, "How much energy has been measured at this
frequency? ", one would ask, "How structured is the signal at this frequency? Is this
consistent with a target? " The auditory-motivated zero crossings with peak amplitudes
(ZCPA) algorithm forms the starting-point for this study.
Next, matters related to quantitative system performance analysis are addressed, such
as how often a system will fail to detect a signal in particular conditions, or how much
energy is required to guarantee a certain probability of detection. A suite of optimal
temporal receivers is designed and is subsequently evaluated using the same kinds of
synthetic signal used to assess power-based systems: Gaussian processes and sinusoids.
The final area of work considers how discrete components on a sonar signal display,
such as tonals and transients, can be identified and organised according to auditory
scene analysis principles. Two algorithms are presented and evaluated using synthetic
signals: one is designed to track a tonal through transient events, and the other attempts
to identify groups of comodulated tonals against a noise background. A demonstration
of each algorithm is provided for recorded sonar signals.
Metadata
Awarding institution: | University of Sheffield |
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Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Computer Science (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > Computer Science (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.555508 |
Depositing User: | EThOS Import Sheffield |
Date Deposited: | 31 May 2016 15:30 |
Last Modified: | 31 May 2016 15:30 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:12827 |
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