Broadband angle of arrival estimation methods in a polynomial matrix decomposition framework

Stephan Weiss, Mohamed Alrmah, Sangarapillai Lambotharan, John G. McWhirter, Mostafa Kaveh

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

17 Citations (Scopus)

Abstract

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.
Original languageEnglish
Title of host publication2013 IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
PublisherIEEE
Pages109-112
Number of pages4
ISBN (Print)978-1-4673-3144-9
DOIs
Publication statusPublished - 15 Dec 2013
EventThe Fifth IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing - San Martin, France
Duration: 15 Dec 201318 Dec 2013

Conference

ConferenceThe Fifth IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
CountryFrance
CitySan Martin
Period15/12/1318/12/13

Keywords

  • polynomials
  • vectors
  • arrays
  • broadband communication
  • covariance matrices
  • matrix decomposition
  • multiple signal classification

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    Weiss, S., Alrmah, M., Lambotharan, S., McWhirter, J. G., & Kaveh, M. (2013). Broadband angle of arrival estimation methods in a polynomial matrix decomposition framework. In 2013 IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) (pp. 109-112). IEEE. https://doi.org/10.1109/CAMSAP.2013.6714019