Title :
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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-0003-3
DOI :
10.1109/ICASSP.1991.150096
