Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing

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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;
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