Impact of space-time covariance estimation errors on a parahermitian matrix EVD

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2 Citations (Scopus)
41 Downloads (Pure)

Abstract

This paper studies the impact of estimation errors in the sample space-time covariance matrix on its parahermitian matrix eigenvalue decomposition. We provide theoretical bounds for the perturbation of the ground-truth eigenvalues and of the subspaces of their corresponding eigenvectors. We show that for the eigenvalues, the perturbation depends on the norm of the estimation error in the space-time covariance matrix, while the perturbation of eigenvector subspaces can additionally be influenced by the spectral distance of the eigenvalues. We confirm these theoretical results by simulations.
Original languageEnglish
Pages1-5
Number of pages5
Publication statusPublished - 8 Jul 2018
Event10th IEEE Workshop on Sensor Array and Multichannel Signal Processing - Sheffield, United Kingdom
Duration: 8 Jul 201811 Jul 2018

Conference

Conference10th IEEE Workshop on Sensor Array and Multichannel Signal Processing
Abbreviated titleSAM 2018
CountryUnited Kingdom
CitySheffield
Period8/07/1811/07/18

Keywords

  • broadband array processing
  • space-time convariance estimation
  • parahermitian matrix
  • eigenvalue decomposition

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  • Prizes

    Best Student Paper Award

    Connor Delaosa (Recipient), Fraser Kenneth Coutts (Recipient), Jennifer Pestana (Recipient) & Stephan Weiss (Recipient), 2018

    Prize: Prize (including medals and awards)

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    Cite this

    Delaosa, C., Coutts, F. K., Pestana, J., & Weiss, S. (2018). Impact of space-time covariance estimation errors on a parahermitian matrix EVD. 1-5. Paper presented at 10th IEEE Workshop on Sensor Array and Multichannel Signal Processing, Sheffield, United Kingdom.