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
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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1274698
- author
- Christensen, Mads
; Jakobsson, Andreas
LU
and Jensen, Sören
- publishing date
- 2007
- 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
- host publication
- 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
- conference location
- Pacific Grove, CA, United States
- conference dates
- 2007-11-04 - 2007-11-07
- 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
- 2016-04-01 16:58:01
- date last changed
- 2022-01-28 23:22:57
@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}},
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}},
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}},
url = {{http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4487294}},
year = {{2007}},
}