Research on indoor fusion positioning algorithm based on 5G/UWB

Jia Yan; Zhongliang Deng

doi:10.1117/12.3037777

27 September 2024 Research on indoor fusion positioning algorithm based on 5G/UWB

Jia Yan, Zhongliang Deng

Author Affiliations +

Proceedings Volume 13275, Sixth International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024); 132750R (2024) https://doi.org/10.1117/12.3037777
Event: 6th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024), 2024, Wuhan, China

Abstract

This article proposes an indoor 5G and UWB fusion positioning algorithm to address the issues of a single positioning source being easily affected by environmental factors, low positioning accuracy, and poor robustness in indoor environments. This algorithm filters and aligns the data of 5G and UWB positioning units, and sends them to a BP neural network optimized by LM for training, outputting the positioning results. And conduct static and dynamic experiments at a driving school in Zengcheng District, Guangzhou. The experimental results show that under static testing, the LM-BP algorithm has a significant effect on accuracy improvement, with a 32.84% increase compared to the 5G ratio and a 24.24% increase compared to the UWB ratio. Under dynamic testing, the LM-BP algorithm has an 30.81% increase compared to the 5G ratio and an 18.89% increase compared to the UWB ratio.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jia Yan and Zhongliang Deng "Research on indoor fusion positioning algorithm based on 5G/UWB", Proc. SPIE 13275, Sixth International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024), 132750R (27 September 2024); https://doi.org/10.1117/12.3037777

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