Underdetermined wideband DOA estimation of off-grid sources employing the difference co-array concept

Qing Shen; Wei Cui; Wei Liu; Siliang Wu; Yimin D. Zhang; Moeness G. Amin

doi:10.1016/j.sigpro.2016.07.022

Underdetermined wideband DOA estimation of off-grid sources employing the difference co-array concept

Qing Shen
, Wei Cui
, Wei Liu
, Siliang Wu
, Yimin D. Zhang
, Moeness G. Amin

Research output: Journal article publication › Journal article › Academic research › peer-review

76 Citations (Scopus)

Abstract

A wideband off-grid model is proposed to represent dictionary mismatch under the compressive sensing framework exploiting difference co-arrays. A group sparsity based off-grid method is proposed for underdetermined wideband direction of arrival (DOA) estimation which provides improved performance over the existing group sparsity based method with a same search grid. A two-step approach is then proposed which achieves an even better performance with significantly reduced computational complexity.

Original language	English
Pages (from-to)	299-304
Number of pages	6
Journal	Signal Processing
Volume	130
DOIs	https://doi.org/10.1016/j.sigpro.2016.07.022
Publication status	Published - Jan 2017

Keywords

Compressive sensing
Difference co-array
DOA estimation
Group sparsity
Off-Grid

ASJC Scopus subject areas

Control and Systems Engineering
Software
Signal Processing
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

More information

10.1016/j.sigpro.2016.07.022

Cite this

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title = "Underdetermined wideband DOA estimation of off-grid sources employing the difference co-array concept",

abstract = "A wideband off-grid model is proposed to represent dictionary mismatch under the compressive sensing framework exploiting difference co-arrays. A group sparsity based off-grid method is proposed for underdetermined wideband direction of arrival (DOA) estimation which provides improved performance over the existing group sparsity based method with a same search grid. A two-step approach is then proposed which achieves an even better performance with significantly reduced computational complexity.",

keywords = "Compressive sensing, Difference co-array, DOA estimation, Group sparsity, Off-Grid",

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AU - Liu, Wei

AU - Wu, Siliang

AU - Zhang, Yimin D.

AU - Amin, Moeness G.

PY - 2017/1

Y1 - 2017/1

N2 - A wideband off-grid model is proposed to represent dictionary mismatch under the compressive sensing framework exploiting difference co-arrays. A group sparsity based off-grid method is proposed for underdetermined wideband direction of arrival (DOA) estimation which provides improved performance over the existing group sparsity based method with a same search grid. A two-step approach is then proposed which achieves an even better performance with significantly reduced computational complexity.

AB - A wideband off-grid model is proposed to represent dictionary mismatch under the compressive sensing framework exploiting difference co-arrays. A group sparsity based off-grid method is proposed for underdetermined wideband direction of arrival (DOA) estimation which provides improved performance over the existing group sparsity based method with a same search grid. A two-step approach is then proposed which achieves an even better performance with significantly reduced computational complexity.

KW - Compressive sensing

KW - Difference co-array

KW - DOA estimation

KW - Group sparsity

KW - Off-Grid

UR - https://www.scopus.com/pages/publications/84980332375

U2 - 10.1016/j.sigpro.2016.07.022

DO - 10.1016/j.sigpro.2016.07.022

M3 - Journal article

AN - SCOPUS:84980332375

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VL - 130

SP - 299

EP - 304

JO - Signal Processing

JF - Signal Processing

ER -

Underdetermined wideband DOA estimation of off-grid sources employing the difference co-array concept

Abstract

Keywords

ASJC Scopus subject areas

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