PERFORMANCE ANALYSIS OF HIGHER-ORDER ESPRIT FOR LOCALIZATION OF NEAR-FIELD SOURCES

Most existing array processing techniques for estimating the direction s of arrival (DOA's) or signal copy rely heavily on the plane-wave ass umption of far-field sources, When the sources are located relatively close to the array, these techniques may no longer perform satisfactor ily. In this paper, we present an asymptotic performance analysis of a recently proposed ESPRIT-like method for passive localization of near ; field sources, The algorithm, which is based on fourth-order cumulan ts, is formulated for observations collected from a single uniformly s paced linear array, We examine the least-squares version of the algori thm and derive the expressions for the asymptotic variance of the esti mated DOA's (relative to a reference sensor) and estimated ranges of t he sources, We also derive an algorithm independent bound on the asymp totic variance of the estimated parameters. This bound can be used as a measure against the theoretically predicted algorithmic performance. Some insight into the achievable performance of this algorithm is obt ained by numerical evaluation of the bound for several test cases of i nterest, and the results are compared with those obtained by numerical evaluation of the theoretically predicted performance, Monte Carlo si mulations are used to verify the theoretical analysis.