Principal and minor subspace computation with applications

Mohammed A. Hasan, Ali A. Hasan

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

1 Scopus citations

Abstract

Algorithms for computing signal subspace frequency or bearing estimates without eigendecomposition were described. Fast algorithms based on the power method were developed to estimate the principal and minor subspaces of the sample correlation matrices. These subspaces were then utilized to develop high-resolution methods such as MUSIC and ESPRIT for sinusoidal frequency and direction of arrival (DOA) problems. A simple squaring procedure was suggested which provides significant computational saving in comparison with exact eigendecomposition methods.

Original languageEnglish (US)
Title of host publication6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis
PublisherIEEE Computer Society
Pages92-95
Number of pages4
ISBN (Print)0780367030, 9780780367036
DOIs
StatePublished - Jan 1 2001
Event6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Kuala Lumpur, Malaysia
Duration: Aug 13 2001Aug 16 2001

Publication series

Name6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis
Volume1

Other

Other6th International Symposium on Signal Processing and Its Applications, ISSPA 2001
CountryMalaysia
CityKuala Lumpur
Period8/13/018/16/01

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