ASYMPTOTIC PERFORMANCE ANALYSIS OF ESPRIT, HIGHER-ORDER ESPRIT, AND VIRTUAL ESPRIT ALGORITHMS

In this paper, we present an asymptotic performance analysis of three subspace-based methods for direction of arrival (DOA) estimation-the E SPRIT algorithm using second-order statistics, the higher order ESPRIT algorithm using fourth-order cumulants, and the virtual ESPRTT (VESPA ) algorithm using fourth-order cumulants, We examine the least-squares version of these algorithms, derive the expressions for the asymptoti c variance of the estimated DOA's, and use specific examples to compar e the relative performance of the algorithms, Finally, we present Mont e Carlo simulations to validate the theoretical analysis.