Polynomial subspace decomposition for broadband angle of arrival estimation

Mohamed Abubaker Alrmah, Jamie Corr, Ahmed Alzin, Keith Thompson, Stephan Weiss

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

7 Citations (Scopus)
119 Downloads (Pure)

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.
Original languageEnglish
Title of host publication2014 Sensor Signal Processing for Defence (SSPD)
PublisherIEEE
Pages1-5
Number of pages5
ISBN (Print)978-1-4799-5294-6
DOIs
Publication statusPublished - Sep 2014
Event2014 Sensor Signal Processing for Defence - Scotland, Edinburgh, United Kingdom
Duration: 8 Sep 20149 Sep 2014

Conference

Conference2014 Sensor Signal Processing for Defence
CountryUnited Kingdom
CityEdinburgh
Period8/09/149/09/14

Keywords

  • covariance matrices
  • iterative methods
  • matrix decomposition
  • polynomial approximation
  • broadband signal

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    Alrmah, M. A., Corr, J., Alzin, A., Thompson, K., & Weiss, S. (2014). Polynomial subspace decomposition for broadband angle of arrival estimation. In 2014 Sensor Signal Processing for Defence (SSPD) (pp. 1-5). IEEE. https://doi.org/10.1109/SSPD.2014.6943305