Utilizing principal singular vectors for two-dimensional single frequency estimation

H. C. So; Frankie K. W. Chan; C. F. Chan; W. H. Lau

doi:10.1109/ICASSP.2010.5495822

Utilizing principal singular vectors for two-dimensional single frequency estimation

H. C. So
, Frankie K. W. Chan
, C. F. Chan
, W. H. Lau

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

In this paper, frequency estimation of a two-dimensional (2D) cisoid in the presence of additive white Gaussian noise is addressed. By utilizing the rank-one property of the 2D noise-free data matrix, the frequencies are estimated in a separable manner from the principal left and right singular vectors according to an iterative weighted least squares procedure. We have also derived the mean and variance expressions for the frequency estimates, which show that they are approximately unbiased and their accuracy achieves Cramér-Rao lower bound (CRLB) at sufficiently high signal-to-noise ratio conditions. Computer simulation results are included to corroborate the theoretical development as well as to contrast the performance of the proposed algorithm with the weighted phase averager and iterative quadratic maximum likelihood method as well as CRLB. ©2010 IEEE.

Original language	English
Title of host publication	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages	3882-3885
DOIs	https://doi.org/10.1109/ICASSP.2010.5495822
Publication status	Published - 2010
Event	2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, United States Duration: 14 Mar 2010 → 19 Mar 2010 https://ieeexplore.ieee.org/xpl/conhome/5487364/proceeding

Publication series

Name
ISSN (Print)	1520-6149

Conference

Conference	2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Place	United States
City	Dallas
Period	14/03/10 → 19/03/10
Internet address	https://ieeexplore.ieee.org/xpl/conhome/5487364/proceeding

Research Keywords

Frequency estimation
Two-dimensional parameter estimation

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10.1109/ICASSP.2010.5495822

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@inproceedings{c358be377e0742f2ab032eb99a82ad47,

title = "Utilizing principal singular vectors for two-dimensional single frequency estimation",

abstract = "In this paper, frequency estimation of a two-dimensional (2D) cisoid in the presence of additive white Gaussian noise is addressed. By utilizing the rank-one property of the 2D noise-free data matrix, the frequencies are estimated in a separable manner from the principal left and right singular vectors according to an iterative weighted least squares procedure. We have also derived the mean and variance expressions for the frequency estimates, which show that they are approximately unbiased and their accuracy achieves Cram{\'e}r-Rao lower bound (CRLB) at sufficiently high signal-to-noise ratio conditions. Computer simulation results are included to corroborate the theoretical development as well as to contrast the performance of the proposed algorithm with the weighted phase averager and iterative quadratic maximum likelihood method as well as CRLB. {\textcopyright}2010 IEEE.",

keywords = "Frequency estimation, Two-dimensional parameter estimation",

author = "So, \{H. C.\} and Chan, \{Frankie K. W.\} and Chan, \{C. F.\} and Lau, \{W. H.\}",

year = "2010",

doi = "10.1109/ICASSP.2010.5495822",

language = "English",

isbn = "9781424442966",

pages = "3882--3885",

booktitle = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

note = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 ; Conference date: 14-03-2010 Through 19-03-2010",

url = "https://ieeexplore.ieee.org/xpl/conhome/5487364/proceeding",

}

So, HC, Chan, FKW, Chan, CF & Lau, WH 2010, Utilizing principal singular vectors for two-dimensional single frequency estimation. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings., 5495822, pp. 3882-3885, 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, Dallas, Texas, United States, 14/03/10. https://doi.org/10.1109/ICASSP.2010.5495822

Utilizing principal singular vectors for two-dimensional single frequency estimation. / So, H. C.; Chan, Frankie K. W.; Chan, C. F. et al.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2010. p. 3882-3885 5495822.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Utilizing principal singular vectors for two-dimensional single frequency estimation

AU - So, H. C.

AU - Chan, Frankie K. W.

AU - Chan, C. F.

AU - Lau, W. H.

PY - 2010

Y1 - 2010

N2 - In this paper, frequency estimation of a two-dimensional (2D) cisoid in the presence of additive white Gaussian noise is addressed. By utilizing the rank-one property of the 2D noise-free data matrix, the frequencies are estimated in a separable manner from the principal left and right singular vectors according to an iterative weighted least squares procedure. We have also derived the mean and variance expressions for the frequency estimates, which show that they are approximately unbiased and their accuracy achieves Cramér-Rao lower bound (CRLB) at sufficiently high signal-to-noise ratio conditions. Computer simulation results are included to corroborate the theoretical development as well as to contrast the performance of the proposed algorithm with the weighted phase averager and iterative quadratic maximum likelihood method as well as CRLB. ©2010 IEEE.

AB - In this paper, frequency estimation of a two-dimensional (2D) cisoid in the presence of additive white Gaussian noise is addressed. By utilizing the rank-one property of the 2D noise-free data matrix, the frequencies are estimated in a separable manner from the principal left and right singular vectors according to an iterative weighted least squares procedure. We have also derived the mean and variance expressions for the frequency estimates, which show that they are approximately unbiased and their accuracy achieves Cramér-Rao lower bound (CRLB) at sufficiently high signal-to-noise ratio conditions. Computer simulation results are included to corroborate the theoretical development as well as to contrast the performance of the proposed algorithm with the weighted phase averager and iterative quadratic maximum likelihood method as well as CRLB. ©2010 IEEE.

KW - Frequency estimation

KW - Two-dimensional parameter estimation

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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-78049410251&origin=recordpage

U2 - 10.1109/ICASSP.2010.5495822

DO - 10.1109/ICASSP.2010.5495822

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781424442966

SP - 3882

EP - 3885

BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010

Y2 - 14 March 2010 through 19 March 2010

ER -

Utilizing principal singular vectors for two-dimensional single frequency estimation

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