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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.
Original language | English |
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Title of host publication | 2014 Sensor Signal Processing for Defence (SSPD) |
Publisher | IEEE |
Pages | 1-5 |
Number of pages | 5 |
ISBN (Print) | 978-1-4799-5294-6 |
DOIs | |
Publication status | Published - Sept 2014 |
Event | 2014 Sensor Signal Processing for Defence - Scotland, Edinburgh, United Kingdom Duration: 8 Sept 2014 → 9 Sept 2014 |
Conference
Conference | 2014 Sensor Signal Processing for Defence |
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Country/Territory | United Kingdom |
City | Edinburgh |
Period | 8/09/14 → 9/09/14 |
Keywords
- covariance matrices
- iterative methods
- matrix decomposition
- polynomial approximation
- broadband signal
Fingerprint
Dive into the research topics of 'Polynomial subspace decomposition for broadband angle of arrival estimation'. Together they form a unique fingerprint.Projects
- 1 Finished
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Signal Processing Solutions for the Networked Battlespace
Soraghan, J. (Principal Investigator) & Weiss, S. (Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/04/13 → 31/03/18
Project: Research