DocumentCode :
865610
Title :
On polynomial phase signals with time-varying amplitudes
Author :
Zhou, Guotong ; Giannakis, Georgios ; Swami, Ananthram
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
44
Issue :
4
fYear :
1996
fDate :
4/1/1996 12:00:00 AM
Firstpage :
848
Lastpage :
861
Abstract :
We address the parameter estimation problem for a class of nonstationary signals modeled as polynomial phase signals with time-varying amplitudes. Exponentially damped polynomial phase signals are treated as a special case and are analyzed in detail. High-order instantaneous moments provide the basic analytical tool, but links are shown to exist with either the usually employed FFT-based technique or the high-resolution Kumaresan-Tufts (1982), MUSIC, and matrix pencil methods. Asymptotic properties of the relevant estimators are established, Cramer-Rao lower bounds on the amplitude and phase parameter estimates are derived, and computer simulations are carried out to evaluate the performance of various schemes. We focus on parametric modeling of AM-FM signals, mainly because parametric techniques offer parsimony and allow for theoretically unlimited resolution
Keywords :
amplitude estimation; amplitude modulation; fast Fourier transforms; frequency modulation; matrix algebra; phase estimation; polynomials; signal resolution; time-varying systems; AM-FM signals; Cramer-Rao lower bounds; FFT based technique; MUSIC; amplitude parameter estimate; asymptotic properties; computer simulations; exponentially damped polynomial phase signals; high-order instantaneous moments; high-resolution Kumaresan-Tufts method; matrix pencil method; nonstationary signals; parameter estimation; parametric modeling; performance evaluation; phase parameter estimate; polynomial phase signals; signal analysis; time-varying amplitudes; Amplitude estimation; Doppler radar; Frequency modulation; Least squares approximation; Maximum likelihood estimation; Parameter estimation; Parametric statistics; Phase estimation; Polynomials; Signal analysis;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.492538
Filename :
492538
Link To Document :
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