4D Near-Field Source Localization Using Cumulant

Abstract

This paper proposes a new cumulant-based algorithm to jointly estimate four-dimensional (4D) source parameters of multiple near-field narrowband sources. Firstly, this approach proposes a new cross-array, and constructs five high-dimensional Toeplitz matrices using the fourth-order cumulants of some properly chosen sensor outputs; secondly, it forms a parallel factor (PARAFAC) model in the cumulant domain using these matrices, and analyzes the unique low-rank decomposition of this model; thirdly, it jointly estimates the frequency, two-dimensional (2D) directions-of-arrival (DOAs), and range of each near-field source from the matrices via the low-rank three-way array (TWA) decomposition. In comparison with some available methods, the proposed algorithm, which efficiently makes use of the array aperture, can localize sources using sensors. In addition, it requires neither pairing parameters nor multidimensional search. Simulation results are presented to validate the performance of the proposed method.