Title :
Non-asymptotic performance analysis of eigenstructure spectral methods
Author :
Wang, Huili ; Wakefield, Gregory
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Abstract :
A nonasymptotic theoretical analysis for the performance of eigenstructure spectral methods for direction-of-arrival (DOA) estimation is proposed. The performance analysis is based on perturbation analysis of covariance eigenstructure and directions-of-arrival. The performance is expressed in terms of signal-to-noise ratio (SNR), the number of snapshots, and other parameters including source locations, sensor locations, and sensor gains without utilizing asymptotic conditions. From the expression, it is proved that the absolute bias and the variance of MUSIC direction-of-arrival estimation is inversely proportional to signal-to-noise ratio and to the number of snapshots. Simulations confirm the inverse proportional relationship under conditions including a small-number of snapshots
Keywords :
eigenvalues and eigenfunctions; parameter estimation; signal processing; spectral analysis; MUSIC; covariance eigenstructure; direction-of-arrival estimation; eigenstructure spectral methods; nonasymptotic theoretical analysis; performance analysis; perturbation analysis; sensor gains; sensor locations; signal-to-noise ratio; snapshots; source locations; Covariance matrix; Direction of arrival estimation; Eigenvalues and eigenfunctions; Inverse problems; Maximum likelihood estimation; Multiple signal classification; Performance analysis; Performance gain; Position measurement; Sensor arrays; Signal to noise ratio; Vectors;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
DOI :
10.1109/ICASSP.1990.116142
