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

^*Corresponding author for this work

School of Information and Electronics

Research output: Contribution to journal › Article › peer-review

69 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 - 1 Jan 2017

Keywords

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

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10.1016/j.sigpro.2016.07.022

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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.",

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AU - Cui, Wei

AU - Liu, Wei

AU - Wu, Siliang

AU - Zhang, Yimin D.

AU - Amin, Moeness G.

PY - 2017/1/1

Y1 - 2017/1/1

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 - DOA estimation

KW - Difference co-array

KW - Group sparsity

KW - Off-Grid

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SP - 299

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JO - Signal Processing

JF - Signal Processing

ER -

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

Abstract

Keywords

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