Direction-of-Arrival Estimation via Sparse Bayesian Learning Exploiting Hierarchical Priors with Low Complexity

For direction-of-arrival (DOA) estimation problems in a sparse domain, sparse Bayesian learning (SBL) is highly favored by researchers owing to its excellent estimation performance. However, traditional SBL-based methods always assign Gaussian priors to parameters to be solved, leading to moderate s...

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Bibliographic Details
Main Authors: Ninghui Li, Xiaokuan Zhang, Fan Lv, Binfeng Zong
Format: Article
Language:English
Published: MDPI AG 2024-04-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/24/7/2336