Underdetermined Wideband DOA Estimation for Off-Grid Sources with Coprime Array Using Sparse Bayesian Learning

Underdetermined Wideband DOA Estimation for Off-Grid Sources with Coprime Array Using Sparse Bayesian Learning

Sparse Bayesian learning (SBL) is applied to the coprime array for underdetermined wideband direction of arrival (DOA) estimation. Using the augmented covariance matrix, the coprime array can achieve a higher number of degrees of freedom (DOFs) to resolve more sources than the number of physical sen...

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Bibliographic Details
Main Authors: Yanhua Qin, Yumin Liu, Jianyi Liu, Zhongyuan Yu
Format: Article
Language:English
Published: MDPI AG 2018-01-01
Series:Sensors
Subjects:
coprime array
direction of arrival estimation
degrees of freedom
Sparse Bayesian learning
sparse signal representation
off-grid sources
Online Access:http://www.mdpi.com/1424-8220/18/1/253

Internet

http://www.mdpi.com/1424-8220/18/1/253

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