Paper Info
Title
A Second-Order Statistics-Based Mixed Sources Localization Method With Symmetric Sparse Arrays
Abstract
This letter proposes a localization method for mixed far-field (FF) and near-field (NF) sources based on second-order statistics (SOS) with generalized symmetric sparse linear arrays. First, the DOAs of the FF sources are estimated by using MUSIC method. Then, we use the oblique projection technique to isolate the NF sources from the FF ones and the atomic norm minimization is employed to retrieve the DOAs of the NF sources. Finally, the range information of the NF sources are determined by one-dimensional searching. To against the effect of finite measurements, an iterative procedure is employed to alternatively updating the DOA and range information of NF sources and the oblique projector. Closed-form expression of Crammer-Rao lower bound (CRLB) is derived from the coarray perspective for the sparse arrays. Simulations are carried out to demonstrate the effectiveness of our proposed method.
Year
DOI
Venue
2020
10.1109/LCOMM.2020.2989548
IEEE Communications Letters
Keywords
DocType
Volume
Mixed sources localization,second-order statistics,atomic norm,symmetric sparse arrays
Journal
24
Issue
ISSN
Citations 
8
1089-7798
1
PageRank 
References 
Authors
0.36
0
2
Name
Order
Citations
PageRank
Xiaohuan Wu1288.28
Jun Yan2245.17