Near-Field Source Localization via Symmetric Subarrays

Author

Zhi, Wanjun ; Chia, Michael Yan-Wah

Author_Institution

Inst. for Infocomm Res., Singapore

Volume

14

Issue

6

fYear

2007

fDate

6/1/2007 12:00:00 AM

Firstpage

409

Lastpage

412

Abstract

We propose a near-field source localization algorithm with one-dimensional (1-D) search via symmetric subarrays. By dividing the uniform linear array (ULA) into two symmetric subarrays, the steering vectors of the subarrays yield the 1-D (only bearing-related) property of rotational invariance in signal subspace, which allows for the bearing estimation using the generalized far-field ESPRIT. With the estimated bearing, the range estimation of each source is consequently obtained by defining the 1-D MUSIC spectrum. This algorithm transforms the two-dimensional search involved in the parameter estimation to a 1-D search, and it does not require high-order statistics computation in contrast with the traditional near-field high-order ESPRIT algorithm

Keywords

array signal processing; direction-of-arrival estimation; research initiatives; signal sources; 1-D MUSIC spectrum; ULA; bearing estimation; generalized far-field ESPRIT algorithm; multiple signal classification; near-field source localization algorithm; one-dimensional search; parameter estimation; steering vector; symmetric subarray; uniform linear array; Direction of arrival estimation; Multidimensional systems; Multiple signal classification; Parameter estimation; Partitioning algorithms; Phased arrays; Sensor arrays; Signal processing; Statistics; Vectors; Near field; source localization; symmetric subarray;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2006.888390

Filename

4202630