A Non-Iterative Method for Localization of Mixed Far-Field and Near-Field Narrowband Sources with Symmetric Uniform Linear Array

Abstract

This paper investigates the problem of localizing multiple far-field and near-field narrowband sources impinging on a symmetric uniform linear (ULA) array, and a new rank reduction (RARE) based localization method is proposed by using the second-order statistics of the array data, where the “saturation behavior” encountered in most of localization methods is overcome by a non-iterative procedure. Firstly, the direction-of-arrivals (DOAs) of all incident sources are estimated by using a RARE estimator. Then the ranges estimation and sources classification are achieved through a subspace-based estimator formed from the array correlation matrix. Thirdly, a DOA selection scheme is presented for multiple far-field sources. Finally, the effectiveness of the proposed method are substantiated through numerical examples, and the simulation results demonstrate that the proposed method has remarkable performance for both far-field and near-field sources.