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

Volume

44

Issue

10

fYear

1996

fDate

10/1/1996 12:00:00 AM

Firstpage

2537

Lastpage

2550

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;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.539037

Filename

539037