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Application of the Reiterative MMSE Algorithm to Underwater Acoustics Using Covariance Matrix Tapers for Robustness

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dc.contributor.advisor Wage, Kathleen E
dc.contributor.author Cuprak, Travis
dc.creator Cuprak, Travis
dc.date 2013-01-16
dc.date.accessioned 2013-02-18T17:54:29Z
dc.date.available NO_RESTRICTION en_US
dc.date.available 2013-02-18T17:54:29Z
dc.date.issued 2013-02-18
dc.identifier.uri https://hdl.handle.net/1920/8024
dc.description.abstract Signal detection in underwater acoustics is conventionally performed with the matched filter. The matched filter is simple, efficient, and well understood. Unfortunately, it is also susceptible to poor sidelobe performance in the presence of loud signals. This can lead to signal masking and missed detections. The matched filter may not be able to resolve the arrival time of multiple, closely-spaced signals. The goal of this thesis is to explore the use of a new radar algorithm, known as the Reiterative Minimum Mean Squared Error (RMMSE) Algorithm [1] for use in underwater acoustics. The sensitivity of the RMMSE algorithm to several common sonar distortions is explored. The distortions are simulated and processing results are presented. Algorithm sensitivity is quantified through a measurement of the median sidelobe level of the filter output. It is seen that the RMMSE algorithm suffers from degraded performance in the presence of the simulated distortions, and in some cases the adverse effects of the distortion are severe. Further investigation derives Covariance Matrix Tapers (CMTs) as a robustness enhancement to the RMMSE algorithm. Simulations demonstrate the benefit of RMMSE-CMT processing. In all cases investigated, CMTs successfully mitigate distortion and improve output sidelobe levels. CMTs are also computationally efficient. They are computed once and applied through the use of the Hadamard product (element by element matrix multiplication). The use of CMTs in RMMSE processing is a new contribution to RMMSE literature. Experimental data analysis is also presented. Initial RMMSE processing results show severely degraded algorithm performance- only the strongest signal is visible. RMMSECMT processing reveals the presence of at least three additional signals that are unresolvable in the matched filter and RMMSE sidelobes.
dc.language.iso en en_US
dc.subject adaptive pulse compression en_US
dc.subject active sonar en_US
dc.subject covariance matrix taper en_US
dc.subject adaptive signal processing en_US
dc.subject RMMSE en_US
dc.subject matched filter en_US
dc.title Application of the Reiterative MMSE Algorithm to Underwater Acoustics Using Covariance Matrix Tapers for Robustness en_US
dc.type Thesis en
thesis.degree.name Master of Science in Electrical Engineering en_US
thesis.degree.level Master's en
thesis.degree.discipline Electrical Engineering en
thesis.degree.grantor George Mason University en


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