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Summary: 3032 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 48, NO. 11, NOVEMBER 2000
Rational Invariant Subspace Approximations with
Applications
Mohammed A. Hasan, Member, IEEE, Mahmood R. Azimi-Sadjadi, Senior Member, IEEE, and Ali A. Hasan
Abstract--Subspace methods such as MUSIC, Minimum Norm,
and ESPRIT have gained considerable attention due to their su-
perior performance in sinusoidal and direction-of-arrival (DOA)
estimation, but they are also known to be of high computational
cost. In this paper, new fast algorithms for approximating signal
and noise subspaces and that do not require exact eigendecompo-
sition are presented. These algorithms approximate the required
subspace using rational and power-like methods applied to the di-
rect data or the sample covariance matrix. Several ESPRIT- as well
as MUSIC-type methods are developed based on these approxima-
tions. A substantial computational saving can be gained comparing
with those associated with the eigendecomposition-based methods.
These methods are demonstrated to have performance comparable
to that of MUSIC yet will require fewer computation to obtain the
signal subspace matrix.
Index Terms--DOA, ESPRIT, frequency estimation, minimum
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