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

Subject Categories:

  • Electricity and Magnetism
  • Radiofrequency Wave Propagation

Distribution Statement:

APPROVED FOR PUBLIC RELEASE