Robust Low-Snapshot DOA Estimation for Sparse Arrays via a Hybrid Convolutional Graph Neural Network

Robust Low-Snapshot DOA Estimation for Sparse Arrays via a Hybrid Convolutional Graph Neural Network

We propose a hybrid Convolutional Graph Neural Network (C-GNN) for direction-of-arrival (DOA) estimation in sparse sensor arrays under low-snapshot conditions. The C-GNN architecture combines 1D convolutional layers for local spatial feature extraction with graph convolutional layers for global stru...

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Bibliographic Details
Main Authors: Hongliang Zhu, Hongxi Zhao, Chunshan Bao, Yiran Shi, Wenchao He
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Sensors
Subjects:
direction-of-arrival (DOA) estimation
graph neural network
low snapshots
array signal processing
Online Access:https://www.mdpi.com/1424-8220/25/15/4563
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