Matrix sign algorithm for sinusoidal frequency and DOA estimation problems

Mohammed A Hasan, Jawad A. Hasan

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

Abstract

Fast algorithms based on the matrix sign function are developed to estimate the signal and noise subspaces of the sample correlation matrices. These subspaces are then utilized to develop high resolution methods such as MUSIC and ESPRIT for sinusoidal frequency and direction of arrival (DOA) problems. The main feature of these algorithms is that they generate subspaces that are parameterized by the signal-to-noise ratio (SNR). Significant computational saving will be obtained due to the fast convergence of these higher order iterations and to the fact that subspaces rather than individual eigenvectors are actually computed. Simulations showing the performance of these methods were also presented.

Original languageEnglish (US)
Title of host publicationProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1369-1372
Number of pages4
ISBN (Print)0780344286, 9780780344280
DOIs
StatePublished - Jan 1 1998
Event1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 - Seattle, WA, United States
Duration: May 12 1998May 15 1998

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
ISSN (Print)1520-6149

Other

Other1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
Country/TerritoryUnited States
CitySeattle, WA
Period5/12/985/15/98

Fingerprint

Dive into the research topics of 'Matrix sign algorithm for sinusoidal frequency and DOA estimation problems'. Together they form a unique fingerprint.

Cite this