STOCHASTIC MATCHED FILTERS FOR SIGNAL DETECTION APPLICATIONS
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Authors
Welch, Michelle M.
Subjects
matched filter
stochastic matched filter
non-stationary signals
acoustic signals
detection
stochastic matched filter
non-stationary signals
acoustic signals
detection
Advisors
Fargues, Monique P.
Date of Issue
2022-06
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
The stochastic matched filter (SMF) is a variation of the matched filter that can detect stochastic signals in noisy environments. Some earlier studies suggest that the SMF can be extended to the detection of frequency time-variant (nonstationary) signals, namely wideband modulated sonar in shallow water. This thesis considers the SMF algorithm first proposed by J.-F. Cavasillas in signal detection and estimation scenarios, and investigates its application to narrowband and chirp signals imbedded in white noise. In medium to high signal to noise ratio (SNR) values, results indicate that the SMF is a viable technique for signal detection and estimation, and could be employed in passive, real-time signal detection and estimation scenarios.
Type
Thesis
Description
Series/Report No
Department
Electrical and Computer Engineering (ECE)
Organization
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NPS Report Number
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Citation
Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.