A Near-Field Source Localization Method for Uniform/Sparse Centrally Symmetric Rectangular Arrays
Xiaohuan Wu, Jiang Wang, Yazhou Liu, Jianing Li
Abstract
Most existing near-field (NF) source localization methods are based on uniform/sparse symmetric linear arrays. But planar arrays will be more common in the future. In this paper, we propose an NF source localization method for rectangular array, which can be uniform rectangular array (URA) or centrally symmetric sparse rectangular array (SRA). We first use the forth-order cumulant to formulate a low-rank matrix reconstruction (LRMR) problem for angle estimation, and then, we use 1D-MUSIC to find the range estimates. We also consider the dual problem of the LRMR problem to reduce computations. Our method shows similar estimation accuracy to the maximum likelihood method while enjoys much less computations. Simulations results are provided to demonstrate the advantages of our method.
BibTeX
@inproceedings{icassp2024_anearfieldsource,
title = {A Near-Field Source Localization Method for Uniform/Sparse Centrally Symmetric Rectangular Arrays},
author = {Xiaohuan Wu and Jiang Wang and Yazhou Liu and Jianing Li},
booktitle = {ICASSP 2024},
year = {2024}
}