Polynomial subspace decomposition for broadband angle of arrival estimation

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Alrmah, Mohamed Abubaker and Corr, Jamie and Alzin, Ahmed and Thompson, Keith and Weiss, Stephan; (2014) Polynomial subspace decomposition for broadband angle of arrival estimation. In: 2014 Sensor Signal Processing for Defence (SSPD). IEEE, GBR, pp. 1-5. ISBN 978-1-4799-5294-6 (https://doi.org/10.1109/SSPD.2014.6943305)

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Abstract

In this paper we study the impact of polynomial or broadband subspace decompositions on any subsequent processing, which here uses the example of a broadband angle of arrival estimation technique using a recently proposed polynomial MUSIC (P-MUSIC) algorithm. The subspace decompositions are performed by iterative polynomial EVDs, which differ in their approximations to diagonalise and spectrally majorise s apce-time covariance matrix.We here show that a better diagonalisation has a significant impact on the accuracy of defining broadband signal and noise subspaces, demonstrated by a much higher accuracy of the P-MUSIC spectrum.

ORCID iDs

Alrmah, Mohamed Abubaker, Corr, Jamie ORCID logoORCID: https://orcid.org/0000-0001-9900-0796, Alzin, Ahmed ORCID logoORCID: https://orcid.org/0000-0001-8716-8233, Thompson, Keith ORCID logoORCID: https://orcid.org/0000-0003-0727-7347 and Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206;
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