Statistical analysis of eigenspace-based source location estimates

Author

Xu, Xiao-Liang ; Buckley, Kevin M.

Author_Institution

Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA

fYear

1991

fDate

14-17 Apr 1991

Firstpage

3041

Abstract

A simple and rigorous statistical analysis of location estimates obtained from eigenspace spatial-spectrum based algorithms is presented. Concise and accurate variance expressions of location estimates for MUSIC, MIN-NORM, and FINE are derived. These expressions are valid over a wide range extending down into the resolution threshold region. It is shown that these expressions, though asymptotical, can be accurately applied to limited number of snapshot cases. Bias of location estimates is also briefly discussed. Based on the statistical analysis, a comparison among MUSIC, MIN-NORM, and FINE is made. Variance advantage of FINE over MIN-NORM, and the comparable variance between FINE and MUSIC are analytically proven

Keywords

eigenvalues and eigenfunctions; signal detection; spectral analysis; statistical analysis; FINE; MIN-NORM; MUSIC; eigenspace source location estimates; eigenspace spatial spectrum algorithms; location estimates bias; resolution threshold region; statistical analysis; variance expressions; Computational complexity; Contracts; Multiple signal classification; Narrowband; Performance analysis; Position measurement; Sensor arrays; Sensor phenomena and characterization; Spatial resolution; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on

Conference_Location

Toronto, Ont.

ISSN

1520-6149

Print_ISBN

0-7803-0003-3

Type

conf

DOI

10.1109/ICASSP.1991.150096

Filename

150096