Accession Number:
ADA275016
Title:
Removal of Coherent Extremely Low Frequency (ELF) Background Noise by Adaptive Noise Cancelation
Descriptive Note:
Master's thesis
Corporate Author:
NAVAL POSTGRADUATE SCHOOL MONTEREY CA
Personal Author(s):
Report Date:
1993-09-23
Pagination or Media Count:
72.0
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. Extremely Low FrequencyELF, Adaptive noise cancelation, Sequential Regression AlgorithmSER
Descriptors:
Subject Categories:
- Electricity and Magnetism
- Radiofrequency Wave Propagation