Detection and identification of cyclostationary signals
By: Evandro Luiz da Costa
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1996
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Number of pages: 117
Description: 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.
Notes: Thesis advisor(s): Ralph Hippenstiel,  Roberto Cristi.

"March 1996."

Thesis (M.S. in Electrical Engineering and M.S. in Engineering Acoustics) Naval Postgraduate School, March 1996.

Includes bibliographical references.

"Approved for public release; distribution is unlimited."-Cover.

Also available online.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat reader.

Brazilian Navy author.

dk/dk cc:9116 10/2/96