Picture of neon light reading 'Open'

Discover open research at Strathprints as part of International Open Access Week!

23-29 October 2017 is International Open Access Week. The Strathprints institutional repository is a digital archive of Open Access research outputs, all produced by University of Strathclyde researchers.

Explore recent world leading Open Access research content this Open Access Week from across Strathclyde's many research active faculties: Engineering, Science, Humanities, Arts & Social Sciences and Strathclyde Business School.

Explore all Strathclyde Open Access research outputs...

Polynomial subspace decomposition for broadband angle of arrival estimation

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, pp. 1-5. ISBN 978-1-4799-5294-6

[img]
Preview
Text (Alrmah-etal-SSPD-2014-Polynomial-subspace-decomposition-for-broadband-angle)
Alrmah_etal_SSPD_2014_Polynomial_subspace_decomposition_for_broadband_angle.pdf - Accepted Author Manuscript

Download (201kB) | Preview

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.