Title :
The optimum weight of angle-dependent weighted MUSIC and its approximations
Author :
Xu, Wenyuan ; Kaveh, Mostafa
Author_Institution :
Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA
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
Keywords :
array signal processing; parameter estimation; statistical analysis; SNR; angle-dependent weighted MUSIC; closely spaced sources; optimum weight function; parameter estimators; point statistics; signal-subspace estimators; signal-to-noise ratio; weighted norm MUSIC; Analytical models; Contracts; Covariance matrix; Detectors; Multiple signal classification; Parameter estimation; Robustness; Signal analysis; Signal resolution; Signal to noise ratio; Statistics;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342319