Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing

Coventry, William and Clemente, Carmine and Soraghan, John; (2017) Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing. In: 25th European Signal Processing Conference, EUSIPCO 2017. IEEE, GRC, pp. 2448-2452. ISBN 9780992862671 (https://doi.org/10.23919/EUSIPCO.2017.8081650)

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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.

ORCID iDs

Coventry, William, Clemente, Carmine ORCID logoORCID: https://orcid.org/0000-0002-6665-693X and Soraghan, John ORCID logoORCID: https://orcid.org/0000-0003-4418-7391;
  • Item type:Book Section
    ID code:64085
    Dates:
    Date
    Event
    23 October 2017
    Published
    25 May 2017
    Accepted
    Notes:© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Keywords:spatial smoothing, direction of arrival, DoA, polynomial eigenvalue decomposition, PEVD, Electrical engineering. Electronics Nuclear engineering, Signal Processing
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    University of Strathclyde > University of Strathclyde
    Depositing user: Pure Administrator
    Date deposited:17 May 2018 11:06
    Last modified:06 Dec 2021 01:17
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/64085
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