The problem of estimating the n unknown amplitudes, frequencies and phases of the components of a multisinusoidal signal is addressed in this paper. The proposed methodology theoretically allows the exact identification of the above unknown parameters within an arbitrarily small finite time in the noise-free scenario. The measured signal is processed by a bank of Volterra integral operators with a suitably designed kernel, that yields a set of auxiliary signals which are computable on-line by causal linear filters. These auxiliary signals are in turn used to estimate the frequencies in an adaptive fashion, while the amplitudes and the phases estimates can be calculated by means of algebraic formulas. The effectiveness of the estimation technique is evaluated and compared with other existing finite-time estimators via numerical simulations.
Estimation of Multi-Sinusoidal Signals: A Deadbeat Methodology
PARISINI, Thomas
2016-01-01
Abstract
The problem of estimating the n unknown amplitudes, frequencies and phases of the components of a multisinusoidal signal is addressed in this paper. The proposed methodology theoretically allows the exact identification of the above unknown parameters within an arbitrarily small finite time in the noise-free scenario. The measured signal is processed by a bank of Volterra integral operators with a suitably designed kernel, that yields a set of auxiliary signals which are computable on-line by causal linear filters. These auxiliary signals are in turn used to estimate the frequencies in an adaptive fashion, while the amplitudes and the phases estimates can be calculated by means of algebraic formulas. The effectiveness of the estimation technique is evaluated and compared with other existing finite-time estimators via numerical simulations.File | Dimensione | Formato | |
---|---|---|---|
Chen_Li_Pin_Parisini_CDC16.pdf
Accesso chiuso
Descrizione: Articolo pubblicato
Tipologia:
Documento in Versione Editoriale
Licenza:
Digital Rights Management non definito
Dimensione
261.48 kB
Formato
Adobe PDF
|
261.48 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.