Affiliation of Author(s):电子信息工程学院

Journal:INTERNATIONAL JOURNAL OF ELECTRONICS

Key Words:DOA estimation L-shaped array MUSIC coprime array unfolded coprime array

Abstract:Generally, a coprime L-shaped array (CLsA) is composed of two uniform L-shaped subarrays with larger spacing among inter-element to accomplish the improved direction of arrival (DOA) estimation performance. In this paper, the two subarrays are unfolded to extend the array aperture and the performance of the unfolded CLsA (UCLsA) for two-dimensional (2D) DOA estimation is investigated. In addition, an all array multiple signals classification (AA-MUSIC) algorithm is proposed for the UCLsA. By stacking the received signals of the two subarrays, the ambiguity problem can be avoided on the basis of the coprime property. Simultaneously, due to the combination of the cross-correlation and auto-correlation, the proposed AA-MUSIC algorithm can achieve the full degrees of freedom (DOFs) and obtain more accurate DOA estimates, nevertheless, the expensive total spectral search is entailed. Consequently, a reduced complexity MUSIC (RC-MUSIC) algorithm is proposed to relieve the computational burden. The Cramer-Rao Bounds (CRBs) are utilised as a theoretical benchmark for the lower bound of unbiased estimate. Furthermore, numerical simulations verify the effectiveness and superiority of the AA-MUSIC algorithm and RC-MUSIC method for the UCLsA.

ISSN No.:0020-7217

Translation or Not:no

Date of Publication:2018-01-01

Co-author:弓盼,F70206593

Correspondence Author:zxf