Differentiating random amplitude harmonics from constant amplitude harmonics

Author

Zhou, Guotong

Author_Institution

Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

fYear

1996

fDate

24-26 Jun 1996

Firstpage

428

Lastpage

431

Abstract

Periodograms are useful tools to reveal hidden periodicities in a given time series but the resulting spectral lines have often been associated with constant amplitude harmonics. Possibilities exist where the harmonics actually have non-zero mean random (as opposed to constant) amplitudes because the two can have identical periodograms. Applications exist to support the random amplitude models. Cyclic statistics are employed as effective tools to distinguish constant from random amplitude harmonic models. The algorithms are FFT based and are easy to implement as illustrated by numerical examples

Keywords

fast Fourier transforms; harmonic analysis; random processes; spectral analysis; time series; FFT; constant amplitude harmonics; cyclic statistics; hidden periodicities; nonzero mean random; numerical examples; periodograms; random amplitude harmonics; spectral lines; time series; Acoustic scattering; Additive noise; Amplitude estimation; Maximum likelihood estimation; Particle scattering; Radar scattering; Random processes; Signal processing algorithms; Sonar; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal and Array Processing, 1996. Proceedings., 8th IEEE Signal Processing Workshop on (Cat. No.96TB10004

Conference_Location

Corfu

Print_ISBN

0-8186-7576-4

Type

conf

DOI

10.1109/SSAP.1996.534907

Filename

534907