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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Bibliografische Detailangaben

Hauptverfasser:	Hongliang Zhu, Hongxi Zhao, Chunshan Bao, Yiran Shi, Wenchao He
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2025-07-01
Schriftenreihe:	Sensors
Schlagworte:	direction-of-arrival (DOA) estimation graph neural network low snapshots array signal processing
Online-Zugang:	https://www.mdpi.com/1424-8220/25/15/4563
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