Chen, Boli;
Li, Peng;
Pin, Gilberto;
Parisini, Thomas;
(2016)
Estimation of multi-sinusoidal signals: A deadbeat methodology.
In:
2016 IEEE 55th Conference on Decision and Control (CDC).
(pp. pp. 3763-3768).
IEEE: Las Vegas, NV, USA.
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Abstract
The problem of estimating the n unknown amplitudes, frequencies and phases of the components of a multi-sinusoidal 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.
| Type: | Proceedings paper |
|---|---|
| Title: | Estimation of multi-sinusoidal signals: A deadbeat methodology |
| Event: | 2016 IEEE 55th Conference on Decision and Control (CDC) |
| Location: | Las Vegas, NV, USA |
| Dates: | 12 Dec 2016 - 14 Dec 2016 |
| ISBN-13: | 9781509018376 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/cdc.2016.7798836 |
| Publisher version: | https://doi.org/10.1109/CDC.2016.7798836 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Kernel, Frequency estimation, Phase locked loops, Observers, Pins, Harmonic analysis |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10189792 |
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