Title :
Asymptotic performance analysis of ESPRIT, higher order ESPRIT, and virtual ESPRIT algorithms
Author :
Yuen, Norman ; Friedlander, Benjamin
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA
fDate :
10/1/1996 12:00:00 AM
Abstract :
In this paper, we present an asymptotic performance analysis of three subspace-based methods for direction of arrival (DOA) estimation-the ESPRIT algorithm using second order statistics, the higher order ESPRIT algorithm using fourth-order cumulants, and the virtual ESPRIT (VESPA) algorithm using fourth-order cumulants. We examine the least-squares version of these algorithms, derive the expressions for the asymptotic variance of the estimated DOAs, and use specific examples to compare the relative performance of the algorithms. Finally, we present Monte Carlo simulations to validate the theoretical analysis
Keywords :
Monte Carlo methods; direction-of-arrival estimation; higher order statistics; least squares approximations; DOA; ESPRIT algorithm; Monte Carlo simulations; VESPA; asymptotic performance analysis; asymptotic variance; direction of arrival; fourth-order cumulants; higher order ESPRIT algorithm; least-squares version; second order statistics; subspace-based methods; virtual ESPRIT algorithms; Algorithm design and analysis; Analytical models; Direction of arrival estimation; Equations; Higher order statistics; Multiple signal classification; Performance analysis; Phased arrays; Sensor arrays; Signal processing algorithms;
Journal_Title :
Signal Processing, IEEE Transactions on
