Direction-of-Arrival Estimation with Coarray ESPRIT for Coprime Array

被引:67
|
作者
Zhou, Chengwei [1 ]
Zhou, Jinfang [1 ]
机构
[1] Zhejiang Univ, Coll Informat Sci & Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China
来源
SENSORS | 2017年 / 17卷 / 08期
基金
中国国家自然科学基金;
关键词
coprime array; DOA estimation; ESPRIT; off-grid; virtual sensor; COVARIANCE-MATRIX RECONSTRUCTION; COMPRESSIVE SENSING KERNEL; SPARSE RECONSTRUCTION; LINEAR ARRAYS;
D O I
10.3390/s17081779
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
A coprime array is capable of achieving more degrees-of-freedom for direction-of-arrival (DOA) estimation than a uniform linear array when utilizing the same number of sensors. However, existing algorithms exploiting coprime array usually adopt predefined spatial sampling grids for optimization problem design or include spectrum peak search process for DOA estimation, resulting in the contradiction between estimation performance and computational complexity. To address this problem, we introduce the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) to the coprime coarray domain, and propose a novel coarray ESPRIT-based DOA estimation algorithm to efficiently retrieve the off-grid DOAs. Specifically, the coprime coarray statistics are derived according to the received signals from a coprime array to ensure the degrees-of-freedom (DOF) superiority, where a pair of shift invariant uniform linear subarrays is extracted. The rotational invariance of the signal subspaces corresponding to the underlying subarrays is then investigated based on the coprime coarray covariance matrix, and the incorporation of ESPRIT in the coarray domain makes it feasible to formulate the closed-form solution for DOA estimation. Theoretical analyses and simulation results verify the efficiency and the effectiveness of the proposed DOA estimation algorithm.
引用
收藏
页数:17
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