An Integrated Localization Method for Mixed Near-Field and Far-Field Sources Based on Mixed-Order Statistic

EasyChair Preprint 8135

Abstract

This paper considers the integrated localization for the mixed near-field (NF) and far-field (FF) sources using the uniform linear array (ULA). With the help of the polynomial rooting methods and the propagator, an efficient algorithm is proposed to provide an integrated estimation of the direction of arrival (DOA) and the ranges of the sources. It takes low computational burden without the requirements that separating the DOA and range information or pre-classification of the sources. We first construct two special fourth-order cumulant matrices using the received array data, then extract the prior-electrical parameters related to the array elements by its steering matrix, and finally carry out parameter matching and classification. Besides, the proposed algorithm eliminates the need for tedious eigenvalue decomposition and spectral search steps, and has almost no aperture loss. Eventually, several simulation results show that the proposed algorithm has lower computational complexity under an acceptable accuracy, compared to the state-of-the-art methods.

Keyphrases: Mixed sources, Mixed-order statistic, Sources localization, array signal processing

@booklet{EasyChair:8135,
  author    = {Xile Li and Yangming Lai and Shixing Yang and Wei Yi},
  title     = {An Integrated Localization Method for Mixed Near-Field and Far-Field Sources Based on Mixed-Order Statistic},
  howpublished = {EasyChair Preprint 8135},
  year      = {EasyChair, 2022}}