MULTI-SOURCE MFP WITH THE MULTI-VALUED BARTLETT PROCESSOR
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Authors
Lee, Chungheon
Subjects
matched field processing
localization
shallow water
localization
shallow water
Advisors
Gemba, Kay L.
Seong, Woojae, Seoul National University
Date of Issue
2023-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
This study explores underwater source localization, focusing on matched field processing (MFP). The research identifies the challenges of localizing underwater sources and highlights MFP evolution and advantages. The aim is to comprehensively understand MFP, including its theoretical frameworks, algorithms, and mathematical representations. The methods employed offer insights into the performance of two processors through detailed explanations, simulations, and experimental data processing. The results demonstrate the advantage of the multi-valued Bartlett (MVB) processor over the Bartlett processor when localizing a weak signal to a strong signal in a challenging scenario. The study concludes with recommendations for further exploration and validation of advantages offered by the MVB processor, emphasizing its potential in identifying and localizing weak signals in complex, multi-source environments. We investigate averaging Bartlett with particular subspaces of the MVB processor on the dB scale. This inherently nonlinear technique significantly improved the localization of the weaker source, capitalizing on the distinct sidelobe configurations of the two processors. In conclusion, this research advocates for an extended exploration into the capabilities of the MVB processor. The spotlight remains on its promising potential to identify and pinpoint weak signals amid the intricate tapestry of multi-source underwater domains.
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Thesis
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Distribution Statement
Approved for public release. Distribution is unlimited.
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Copyright is reserved by the copyright owner.