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 proceeding › Chapter (peer-reviewed)

6 Citations (Scopus)

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.
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 2014 → 9 Sep 2014

Conference

Conference2014 Sensor Signal Processing for Defence
CountryUnited Kingdom
CityEdinburgh
Period8/09/14 → 9/09/14

Fingerprint

Polynomials
Decomposition
Covariance matrix
Processing

Keywords

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

Cite this

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
Alrmah, Mohamed Abubaker ; Corr, Jamie ; Alzin, Ahmed ; Thompson, Keith ; Weiss, Stephan. / Polynomial subspace decomposition for broadband angle of arrival estimation. 2014 Sensor Signal Processing for Defence (SSPD). IEEE, 2014. pp. 1-5
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Alrmah, MA, 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). IEEE, pp. 1-5, 2014 Sensor Signal Processing for Defence, Edinburgh, United Kingdom, 8/09/14. https://doi.org/10.1109/SSPD.2014.6943305

Polynomial subspace decomposition for broadband angle of arrival estimation. / Alrmah, Mohamed Abubaker; Corr, Jamie; Alzin, Ahmed; Thompson, Keith; Weiss, Stephan.

2014 Sensor Signal Processing for Defence (SSPD). IEEE, 2014. p. 1-5.

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

TY - CHAP

T1 - Polynomial subspace decomposition for broadband angle of arrival estimation

AU - Alrmah, Mohamed Abubaker

AU - Corr, Jamie

AU - Alzin, Ahmed

AU - Thompson, Keith

AU - Weiss, Stephan

PY - 2014/9

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N2 - 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.

AB - 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.

KW - covariance matrices

KW - iterative methods

KW - matrix decomposition

KW - polynomial approximation

KW - broadband signal

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BT - 2014 Sensor Signal Processing for Defence (SSPD)

PB - IEEE

ER -

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

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