Optimum weight of angle-dependent weighted MUSIC and its approximations

Wenyuan Xu, Mostafa Kaveh

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

1 Scopus citations

Abstract

Angle-Dependent Weighted MUSIC or Weighted Norm MUSIC is a broad class of MUSIC-like parameter estimators which includes as special case the standard `spectral' MUSIC. Based on a general approach for deriving the point statistics of the signal-subspace estimators, the relation between the large-sample moments of MUSIC and Angle-Dependent Weighted MUSIC is presented in this paper. The optimum weight function resulting in the estimator with zero bias of order N-1 is derived. The approximate realizations of this optimum estimator in a parametric subclass of Angle-Dependent Weighted MUSIC for arrays measuring closely spaced sources are discussed. Simulation examples verify the theoretical analysis and demonstrate the proposed estimators have small estimation biases over a wide range of signal-to-noise ratio.

Original languageEnglish (US)
Title of host publicationConference Record of the Asilomar Conference of Signals, Systems & Computers
PublisherPubl by IEEE
Pages1357-1361
Number of pages5
ISBN (Print)0818641207
StatePublished - Dec 1 1993
EventProceedings of the 27th Asilomar Conference on Signals, Systems & Computers - Pacific Grove, CA, USA
Duration: Nov 1 1993Nov 3 1993

Publication series

NameConference Record of the Asilomar Conference of Signals, Systems & Computers
Volume2
ISSN (Print)1058-6393

Other

OtherProceedings of the 27th Asilomar Conference on Signals, Systems & Computers
CityPacific Grove, CA, USA
Period11/1/9311/3/93

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