DOA Estimation Method for Vector Hydrophones Based on Sparse Bayesian Learning

DOA Estimation Method for Vector Hydrophones Based on Sparse Bayesian Learning

Through extensive literature review, it has been found that sparse Bayesian learning (SBL) is mainly applied to traditional scalar hydrophones and is rarely applied to vector hydrophones. This article proposes a direction of arrival (DOA) estimation method for vector hydrophones based on SBL (Vector...

Full description

Saved in:
Bibliographic Details
Main Authors: Hongyan Wang, Yanping Bai, Jing Ren, Peng Wang, Ting Xu, Wendong Zhang, Guojun Zhang
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Sensors
Subjects:
DOA estimation
vector hydrophone
compressed sensing
sparse Bayesian learning
Online Access:https://www.mdpi.com/1424-8220/24/19/6439
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/24/19/6439

Similar Items