Convolutional Neural Networks for Direction of Arrival Estimation Compared to Classical Estimators and Bounds

Convolutional Neural Networks for Direction of Arrival Estimation Compared to Classical Estimators and Bounds

Recently, there has been a proliferation of applied machine learning (ML) research, including the use of convolutional neural networks (CNNs) for direction of arrival (DoA) estimation. With the increasing amount of research in this area, it is important to balance the performance and computational c...

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Bibliographic Details
Main Authors: Christopher J. Bell, Kaushallya Adhikari, Andrew Brown
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
direction of arrival
multiple signal classification
Cramer-Rao lower bound
regression
perturbed array
Online Access:https://ieeexplore.ieee.org/document/10872920/
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