Fast algorithms for signal subspace estimation with applications to DOA estimation

Mohammed A Hasan, Jawad A K Hasan

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

Abstract

Subspace methods such as MUSIC and Minimum Norm estimators are popular for their high resolution property in sinusoidal and directions of arrival (DOA) estimation, but they are also known to be of high computational demand. In this paper, new fast algorithms for DOA and sinusoidal frequency estimation which do not require the exact eigendecomposition of the covariance matrix are presented. These algorithms approximate the required subspace using rational and power-like methods applied to the sample covariance matrix. A substantial computational saving would be gained compared with those associated with the eigendecomposition-based methods. Simulations results have shown that these approximated estimators have comparable performance at low signal-to-noise ratio (SNR) to their standard counterparts and are robust against overestimating the number of impinging signals.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Symposium on Circuits and Systems
PublisherIEEE
ISBN (Print)0780354710
StatePublished - Jan 1 1999
EventProceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99 - Orlando, FL, USA
Duration: May 30 1999Jun 2 1999

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume3
ISSN (Print)0271-4310

Other

OtherProceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99
CityOrlando, FL, USA
Period5/30/996/2/99

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