Detection and identification of cyclostationary signals

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detectionidentif00cost.pdf (4.24 MB)
Authors
Costa, Evandro Luiz da.
Subjects
Cyclic spectral analysis
FFT accumulation method
Strip spectral correlation algorithm
Advisors
Cristi, Roberto
Hippenstiel, Ralph
Date of Issue
1996-03
Date
March 1996
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
Propeller noise can be modeled as an amplitude modulated (AM) signal. Cyclic Spectral Analysis has been used successfully to detect the presence of analog and digitally modulated signals in communication systems. It can also identify the type of modulation. Programs for Signal Processing based on compiled languages such as FORTRAN or C are not user friendly, and MATLAB based programs have become the de facto language and tools for signal processing engineers worldwide. This thesis describes the implementation in MATLAB of two fast methods of computing the Spectral Correlation Density (SCD) Function estimate, the FFT Accumulation Method (FAM) and the Strip Spectral Correlation Algorithm (SSCA), to perform Cyclic Analysis. Both methods are based on the Fast Fourier Transform (FFT) algorithm. The results are presented and areas of possible enhancement for propeller noise detection and identification are discussed.
Type
Thesis
Description
URI
https://hdl.handle.net/10945/8241
Series/Report No
Department
Department of Electrical and Computer Engineering
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Funder
Format
117 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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Copyright is reserved by the copyright owner
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