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Sinusoidal Order Estimation using the Subspace Orthogonality and Shift-Invariance Properties

Christensen, Mads; Jakobsson, Andreas LU and Jensen, Sören (2007) 41st Asilomar Conference on Signals, Systems and Computers, 2007 In 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers p.651-655
Abstract
In this paper, we study and compare a number of subspace-based methods for determining the the number of sinusoids in noise. These are based on the subspace orthogonality and and shift-invariance properties that are known from the MUSIC (multiple signal classification) and ESPRIT frequency estimators. The method based on the orthogonality property has not previously appeared in the literature. We compare, in simulations, the various sub-space methods. These show that the subspace methods can estimate the correct order with a high probability for sufficiently high SNRs and number of observations with MUSIC performing the best. Also, unlike the commonly used statistical methods, the subspace methods do not depend on the probability density... (More)
In this paper, we study and compare a number of subspace-based methods for determining the the number of sinusoids in noise. These are based on the subspace orthogonality and and shift-invariance properties that are known from the MUSIC (multiple signal classification) and ESPRIT frequency estimators. The method based on the orthogonality property has not previously appeared in the literature. We compare, in simulations, the various sub-space methods. These show that the subspace methods can estimate the correct order with a high probability for sufficiently high SNRs and number of observations with MUSIC performing the best. Also, unlike the commonly used statistical methods, the subspace methods do not depend on the probability density function of the noise being known. (Less)
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author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
multiple signal classification, sinusoidal order estimation, subspace orthogonality, shift-invariance properties, subspace-based methods, noise sinusoids, MUSIC frequency estimator, ESPRIT frequency estimator, high probability, probability density function
in
2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers
pages
651 - 655
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
41st Asilomar Conference on Signals, Systems and Computers, 2007
external identifiers
  • scopus:50249123439
ISSN
1058-6393
language
English
LU publication?
no
id
0fcc0781-18cd-4a9b-b070-65e419b0c1ec (old id 1274698)
alternative location
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4487294
date added to LUP
2009-05-25 12:22:10
date last changed
2017-06-04 04:27:50
@inproceedings{0fcc0781-18cd-4a9b-b070-65e419b0c1ec,
  abstract     = {In this paper, we study and compare a number of subspace-based methods for determining the the number of sinusoids in noise. These are based on the subspace orthogonality and and shift-invariance properties that are known from the MUSIC (multiple signal classification) and ESPRIT frequency estimators. The method based on the orthogonality property has not previously appeared in the literature. We compare, in simulations, the various sub-space methods. These show that the subspace methods can estimate the correct order with a high probability for sufficiently high SNRs and number of observations with MUSIC performing the best. Also, unlike the commonly used statistical methods, the subspace methods do not depend on the probability density function of the noise being known.},
  author       = {Christensen, Mads and Jakobsson, Andreas and Jensen, Sören},
  booktitle    = {2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers},
  issn         = {1058-6393},
  keyword      = {multiple signal classification,sinusoidal order estimation,subspace orthogonality,shift-invariance properties,subspace-based methods,noise sinusoids,MUSIC frequency estimator,ESPRIT frequency estimator,high probability,probability density function},
  language     = {eng},
  pages        = {651--655},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Sinusoidal Order Estimation using the Subspace Orthogonality and Shift-Invariance Properties},
  year         = {2007},
}