Abstract
Although the periodogram maximizer has good asymptotic properties in the case of a single sinusoid in colored noise, in low SNR conditions and/or in the case of small sample size, the data need to be prewhitened in order for the periodogram maximizer be likely to occur near the true frequency. In this paper we derive an efficient least squares algorithm for estimating the frequencies, amplitudes, phases and autoregressive parameters for a sum of sinusoids in complex autoregressive noise. The procedure is seen to be a generalization of the Levinson-Durbin algorithm, an efficient technique for estimating the parameters in an autoregression.
| Language | English |
|---|---|
| Title of host publication | Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC |
| Editors | Michael B. Matthews |
| Place of Publication | Piscataway, NJ |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 636-640 |
| Number of pages | 5 |
| ISBN (Print) | 9781424421107 |
| DOIs | |
| Publication status | Published - 2007 |
| Event | 41st Asilomar Conference on Signals, Systems and Computers, ACSSC - Pacific Grove, CA, United States Duration: 4 Nov 2007 → 7 Nov 2007 |
Other
| Other | 41st Asilomar Conference on Signals, Systems and Computers, ACSSC |
|---|---|
| Country | United States |
| City | Pacific Grove, CA |
| Period | 4/11/07 → 7/11/07 |
Bibliographical note
Copyright 2007 IEEE. Reprinted from Conference record of the forty-first Asilomar conference on signals, systems and computers. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.Cite this
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Efficient estimation of the parameters in a sum of complex sinusoids in complex autoregressive noise. / Quinn, B. G.
Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC. ed. / Michael B. Matthews. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2007. p. 636-640 4487291.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › Research › peer-review
TY - GEN
T1 - Efficient estimation of the parameters in a sum of complex sinusoids in complex autoregressive noise
AU - Quinn, B. G.
N1 - Copyright 2007 IEEE. Reprinted from Conference record of the forty-first Asilomar conference on signals, systems and computers. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
PY - 2007
Y1 - 2007
N2 - Although the periodogram maximizer has good asymptotic properties in the case of a single sinusoid in colored noise, in low SNR conditions and/or in the case of small sample size, the data need to be prewhitened in order for the periodogram maximizer be likely to occur near the true frequency. In this paper we derive an efficient least squares algorithm for estimating the frequencies, amplitudes, phases and autoregressive parameters for a sum of sinusoids in complex autoregressive noise. The procedure is seen to be a generalization of the Levinson-Durbin algorithm, an efficient technique for estimating the parameters in an autoregression.
AB - Although the periodogram maximizer has good asymptotic properties in the case of a single sinusoid in colored noise, in low SNR conditions and/or in the case of small sample size, the data need to be prewhitened in order for the periodogram maximizer be likely to occur near the true frequency. In this paper we derive an efficient least squares algorithm for estimating the frequencies, amplitudes, phases and autoregressive parameters for a sum of sinusoids in complex autoregressive noise. The procedure is seen to be a generalization of the Levinson-Durbin algorithm, an efficient technique for estimating the parameters in an autoregression.
UR - http://www.scopus.com/inward/record.url?scp=50249136094&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2007.4487291
DO - 10.1109/ACSSC.2007.4487291
M3 - Conference proceeding contribution
SN - 9781424421107
SP - 636
EP - 640
BT - Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC
A2 - Matthews, Michael B.
PB - Institute of Electrical and Electronics Engineers (IEEE)
CY - Piscataway, NJ
ER -