Removal of coherent extremely low frequency (ELF) background noise by adaptive noise cancelation
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Authors
Strange, Samuel J.
Subjects
Extremely Low Frequency (ELF)
Adaptive Noise Cancelation
Sequential Regression Algorithm (SER)
Adaptive Noise Cancelation
Sequential Regression Algorithm (SER)
Advisors
Farley, Danny G.
Najmi, Amir-H.
Date of Issue
1993-09
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
The use of the Sequential Regression Algorithm (SER) to coherently remove background noise from an ELF sensor is presented. The SER algorithm is described for a multi-channel application in order to cancel coherent portions of reference sensors from a primary sensor. The algorithm adaptively accounts for differences between two parallel array platforms for the purpose of coherent subtraction. A section on likelihood ratio detector schemes for detecting narrowband signals is also presented. This work is in support of a submerged ELF sensor array project run by the Johns Hopkins University Applied Physics Lab
Type
Thesis
Description
Series/Report No
Department
Systems Engineering (SE)
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Funder
Format
66 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.