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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.
|Title of host publication||2014 Sensor Signal Processing for Defence (SSPD)|
|Number of pages||5|
|Publication status||Published - Sep 2014|
|Event||2014 Sensor Signal Processing for Defence - Scotland, Edinburgh, United Kingdom|
Duration: 8 Sep 2014 → 9 Sep 2014
|Conference||2014 Sensor Signal Processing for Defence|
|Period||8/09/14 → 9/09/14|
- covariance matrices
- iterative methods
- matrix decomposition
- polynomial approximation
- broadband signal
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- 1 Finished
Soraghan, J. & Weiss, S.
1/04/13 → 31/03/18