Sparse Bayesian learning for off-grid DOA estimation with nested arrays

被引：56

作者：

Chen, Fangfang ^{[1
]}

Dai, Jisheng ^{[1
]}

Hu, Nan ^{[2
]}

Ye, Zhongfu ^{[3
]}

机构：

[1] Jiangsu Univ, Dept Elect Engn, Zhenjiang 212013, Peoples R China

[2] Soochow Univ, Sch Elect & Informat Engn, Suzhou 215006, Peoples R China

[3] Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Hefei 230027, Anhui, Peoples R China

来源：

DIGITAL SIGNAL PROCESSING | 2018年 / 82卷

基金：

中国国家自然科学基金;

关键词：

Sparse Bayesian learning (SBL); DOA estimation; Nested array; Off-grid; ARRIVAL ESTIMATION; SOURCE LOCALIZATION; PERSPECTIVE;

D O I：

10.1016/j.dsp.2018.08.004

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The existing off-grid sparse Bayesian learning (SBL) DOA estimation method for nested arrays suffers from two major drawbacks: reduced array aperture and high modeling error. To solve these issues, a new data model formulation is first presented in this paper, in which we take the noise variance as a part of the unknown signal of interest, so as to learn its value by the Bayesian inference inherently. Then, we provide a novel grid refining procedure to eliminate the modeling error caused by off-grid gap, where we consider the locations of grid points as adjustable parameters and proceed to refine the grid point iteratively. Simulation results demonstrate that our method significantly improves the DOA estimation performance especially using a coarse grid. (C) 2018 Elsevier Inc. All rights reserved.

引用

页码：187 / 193

页数：7

共 30 条

[1]

Ahmed A, 2017, IEEE RAD CONF, P998, DOI 10.1109/RADAR.2017.7944349

[2] Bayesian Compressive Sensing Using Laplace Priors [J].

Babacan, S. Derin ;

Molina, Rafael ;

Katsaggelos, Aggelos K. .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2010, 19 (01) :53-63

[3] Efficient direction of arrival estimation based on sparse covariance fitting criterion with modeling mismatch [J].

Cai, Shu ;

Wang, Gang ;

Zhang, Jun ;

Wong, Kai-Kit ;

Zhu, Hongbo .

SIGNAL PROCESSING, 2017, 137 :264-273

[4] HIGH-RESOLUTION FREQUENCY-WAVENUMBER SPECTRUM ANALYSIS [J].

CAPON, J .

PROCEEDINGS OF THE IEEE, 1969, 57 (08) :1408-&

[5] FDD Massive MIMO Channel Estimation With Arbitrary 2D-Array Geometry [J].

Dai, Jisheng ;

Liu, An ;

Lau, Vincent K. N. .

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2018, 66 (10) :2584-2599

[6] Sparse Bayesian Learning Approach for Outlier-Resistant Direction-of-Arrival Estimation [J].

Dai, Jisheng ;

So, Hing Cheung .

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2018, 66 (03) :744-756

[7] Root Sparse Bayesian Learning for Off-Grid DOA Estimation [J].

Dai, Jisheng ;

Bao, Xu ;

Xu, Weichao ;

Chang, Chunqi .

IEEE SIGNAL PROCESSING LETTERS, 2017, 24 (01) :46-50

[8] Direction-of-Arrival Estimation Via Real-Valued Sparse Representation [J].

Dai, Jisheng ;

Xu, Xin ;

Zhao, Dean .

IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, 2013, 12 :376-379

[9] Improved Source Number Detection and Direction Estimation With Nested Arrays and ULAs Using Jackknifing [J].

Han, Keyong ;

Nehorai, Arye .

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2013, 61 (23) :6118-6128

[10] THE UNIFYING ROLE OF THE COARRAY IN APERTURE SYNTHESIS FOR COHERENT AND INCOHERENT IMAGING [J].

HOCTOR, RT ;

KASSAM, SA .

PROCEEDINGS OF THE IEEE, 1990, 78 (04) :735-752

← 1 2 3 →