RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems
In UWB-based indoor positioning research, NLOS signals severely degrade localization accuracy. To address the NLOS/LOS discrimination challenge, this paper proposes the RIM-Net model, which enhances CIR signal feature learning by integrating residual blocks and LSTM architectures. Unlike conventiona...
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| Main Authors: | Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11098758/ |
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