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, 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
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Item type: Book Section ID code: 53361 Dates: DateEventSeptember 2014PublishedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 12 Jun 2015 14:21 Last modified: 01 Feb 2025 05:23 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/53361