MF-Pnet: Deep Learning-Based Multi-Narrowband FM Signal Fusion for Enhanced Positioning

This paper proposes MF-Pnet, a deep learning-based positioning method designed to address the limited utilization of informative features in existing FM signal positioning approaches. Unlike prior methods that process the wideband FM signal as a whole, MF-Pnet extracts and fuses multiple narrowband...

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Autors principals:	Shilian Zheng, Xinjiang Qiu, Luxin Zhang, Quan Lin, Keqiang Yue, Zhijin Zhao
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2026-01-01
Col·lecció:	IEEE Transactions on Machine Learning in Communications and Networking
Matèries:	FM signal positioning deep learning feature fusion convolutional neural network
Accés en línia:	https://ieeexplore.ieee.org/document/11429040/
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