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A large family of broadband angle of arrival estimation algorithms are based on the coherent signal subspace (CSS) method, whereby focussing matrices appropriately align covariance matrices across narrowband frequency bins. In this paper, we analyse an auto-focussing approach in the framework of polynomial covariance matrix decompositions, leading to comparisons to two recently proposed polynomial multiple signal classification (MUSIC) algorithms. The analysis is complemented with numerical simulations.
|Title of host publication||2013 IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)|
|Number of pages||4|
|Publication status||Published - 15 Dec 2013|
|Event||The Fifth IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing - San Martin, France|
Duration: 15 Dec 2013 → 18 Dec 2013
|Conference||The Fifth IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing|
|Period||15/12/13 → 18/12/13|
- broadband communication
- covariance matrices
- matrix decomposition
- multiple signal classification
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1/04/13 → 31/03/18