Off-Grid DoA Estimation via Two-Stage Cascaded Neural Network

Off-Grid DoA Estimation via Two-Stage Cascaded Neural Network

This paper introduces an off-grid DoA estimation via two-stage cascaded network which can resolve a mismatch between true direction-of-arrival (DoA) and discrete angular grid. In the first-stage network, the initial DoAs are estimated with a convolutional neural network (CNN), where initial DoAs are...

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Bibliographic Details
Main Authors: Hyeonjin Chung, Hyeongwook Seo, Jeungmin Joo, Dongkeun Lee, Sunwoo Kim
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Energies
Subjects:
off-grid direction-of-arrival (DoA) estimation
machine learning
cascaded neural network
convolutional neural network (CNN)
deep neural network (DNN)
sparse representation
Online Access:https://www.mdpi.com/1996-1073/14/1/228

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