Estimation and statistical analysis of exponential polynomial signals

We derive and analyze a suboptimal algorithm for estimating the unknown parameters of an exponential polynomial signal (EPS) model. The EPS model represents a signal as an exponent raised to a complex polynomial of time. That is, the phase and the logarithm of the amplitude are approximated as finit...

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Veröffentlicht in:	IEEE transactions on signal processing 1998-11, Vol.46 (11), p.3127-3130
Hauptverfasser:	Golden, S., Friedlander, B.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Amplitude estimation Applied sciences Chirp Detection, estimation, filtering, equalization, prediction Exact sciences and technology Information, signal and communications theory Maximum likelihood estimation Parameter estimation Phase estimation Polynomials Signal analysis Signal and communications theory Signal, noise Statistical analysis Taylor series Telecommunications and information theory
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Beschreibung
Zusammenfassung:	We derive and analyze a suboptimal algorithm for estimating the unknown parameters of an exponential polynomial signal (EPS) model. The EPS model represents a signal as an exponent raised to a complex polynomial of time. That is, the phase and the logarithm of the amplitude are approximated as finite-order polynomials of time.
ISSN:	1053-587X 1941-0476
DOI:	10.1109/78.726830