Off-grid DOA estimation using improved root sparse Bayesian learning for non-uniform linear arrays

Off-grid DOA estimation using improved root sparse Bayesian learning for non-uniform linear arrays

Abstract This paper concerns direction of arrival (DOA) estimation based on a sparse Bayesian learning (SBL) approach. We address two inherent problems of this class of DOA estimation methods: (i) a predefined dictionary can generate off-grid problems to a SBL DOA estimator; (ii) a parametric prior...

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Bibliographic Details
Main Authors: Jiajun Shen, Fulvio Gini, Maria Sabrina Greco, Tian Zhou
Format: Article
Language:English
Published: SpringerOpen 2023-03-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Off-grid DOA estimation
Non-uniform linear array (NULA)
Sparse Bayesian learning
Constant false alarm rate
Polynomial rooting
Cramér-Rao bound (CRB)
Online Access:https://doi.org/10.1186/s13634-023-00991-7

Internet

https://doi.org/10.1186/s13634-023-00991-7

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