Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

4 Citations (Scopus)

Abstract

Direction of arrival algorithms which exploit the eigenstructure of the spatial covariance matrix (such as MUSIC) encounter difficulties in the presence of strongly correlated sources. Since the broadband polynomial MUSIC is an extension of the narrowband version, it is unsurprising that the same issues arise. In this paper, we extend the spatial smoothing technique to broadband scenarios via spatially averaging polynomial spacetime covariance matrices. This is shown to restore the rank of the polynomial source covariance matrix. In the application of the polynomial MUSIC algorithm, the spatially smoothed spacetime covariance matrix greatly enhances the direction of arrival estimate in the presence of strongly correlated sources. Simulation results are described shows the performance improvement gained using the new approach compared to the conventional non-smoothed method.

LanguageEnglish
Title of host publication25th European Signal Processing Conference, EUSIPCO 2017
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages2448-2452
Number of pages5
Volume2017-January
ISBN (Electronic)9780992862671
DOIs
Publication statusPublished - 23 Oct 2017
Event25th European Signal Processing Conference, EUSIPCO 2017 - Kos, Greece
Duration: 28 Aug 20172 Sep 2017

Conference

Conference25th European Signal Processing Conference, EUSIPCO 2017
CountryGreece
CityKos
Period28/08/172/09/17

Fingerprint

Covariance matrix
Polynomials
Direction of arrival

Keywords

  • spatial smoothing
  • direction of arrival
  • DoA
  • polynomial eigenvalue decomposition
  • PEVD

Cite this

Coventry, W., Clemente, C., & Soraghan, J. (2017). Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing. In 25th European Signal Processing Conference, EUSIPCO 2017 (Vol. 2017-January, pp. 2448-2452). [8081650] Piscataway, NJ.: IEEE. https://doi.org/10.23919/EUSIPCO.2017.8081650
Coventry, William ; Clemente, Carmine ; Soraghan, John. / Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing. 25th European Signal Processing Conference, EUSIPCO 2017. Vol. 2017-January Piscataway, NJ. : IEEE, 2017. pp. 2448-2452
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Coventry, W, Clemente, C & Soraghan, J 2017, Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing. in 25th European Signal Processing Conference, EUSIPCO 2017. vol. 2017-January, 8081650, IEEE, Piscataway, NJ., pp. 2448-2452, 25th European Signal Processing Conference, EUSIPCO 2017, Kos, Greece, 28/08/17. https://doi.org/10.23919/EUSIPCO.2017.8081650

Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing. / Coventry, William; Clemente, Carmine; Soraghan, John.

25th European Signal Processing Conference, EUSIPCO 2017. Vol. 2017-January Piscataway, NJ. : IEEE, 2017. p. 2448-2452 8081650.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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N2 - Direction of arrival algorithms which exploit the eigenstructure of the spatial covariance matrix (such as MUSIC) encounter difficulties in the presence of strongly correlated sources. Since the broadband polynomial MUSIC is an extension of the narrowband version, it is unsurprising that the same issues arise. In this paper, we extend the spatial smoothing technique to broadband scenarios via spatially averaging polynomial spacetime covariance matrices. This is shown to restore the rank of the polynomial source covariance matrix. In the application of the polynomial MUSIC algorithm, the spatially smoothed spacetime covariance matrix greatly enhances the direction of arrival estimate in the presence of strongly correlated sources. Simulation results are described shows the performance improvement gained using the new approach compared to the conventional non-smoothed method.

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Coventry W, Clemente C, Soraghan J. Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing. In 25th European Signal Processing Conference, EUSIPCO 2017. Vol. 2017-January. Piscataway, NJ.: IEEE. 2017. p. 2448-2452. 8081650 https://doi.org/10.23919/EUSIPCO.2017.8081650