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Improving UWB ranging accuracy via multiple network model with second order motion prediction

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Abstract

With the wide application of ultra-wideband (UWB) ranging technology in industry, production and aerospace, how to improve the accuracy of UWB ranging has become a research hotspot. If the UWB ranging data is treated as sequence data, it is possible to improve the ranging performance by sequence analysis, which has low computation complexity compared to direct UWB signal processing. However, as the UWB ranging data has its inherent properties, existing sequence analysis methods may not achieve good performance on UWB ranging data. In this paper, a two-path deep-learning framework to process, namely the Multiple Network model with Second order motion (MNS), is proposed the improve UWB ranging performance via ranging sequence analysis. The proposed method fuses the target motion prediction via Newton’s laws of motion and error estimation via GRU, LSTM and Bayes. To evaluate our algorithm, we also proposed a method to collect both UWB ranging data and the accurate answer via laser ranging. The collected dataset \(DATA\_TS\), the proposed MNS algorithm, and the trained model are all open sourced to the community to help researchers for further research,please visit(https://github.com/xiaojiuwotongxue/data-store.git). Experiments on \(DATA\_TS\) shows our proposed method outperforms traditional regresion methods significantly.

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Author notes

  1. Yanrong Guo, Xiaoxuan Chen, Hangzai Luo and Sheng Zhong contributed equally to this work.

Authors and Affiliations

  1. School of Information and Technology, Northwest University, Guodu Road, Xi’an, 710127, Shaanxi, China

    Guangwei Xing, Xiaoxuan Chen, Hangzai Luo & Sheng Zhong

  2. Aerospace Computer Design Division, Xi’an Microelectronics Technology Institute, Taibai South Road, Xi’an, 100191, Shaanxi, China

    Yanrong Guo

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  1. Guangwei Xing
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Contributions

GX: conceptualization, methodology, writing–original draft, writing–review and editing. YG: software, methodology, validation and data analysis. XC: writing—original draft, writing–review and editing. HL: investigation, writing–review & editing. SZ: writing–review and editing.

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Correspondence to Xiaoxuan Chen.

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Xing, G., Guo, Y., Chen, X. et al. Improving UWB ranging accuracy via multiple network model with second order motion prediction. Cluster Comput 27, 2261–2272 (2024). https://doi.org/10.1007/s10586-023-04080-0

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  • DOI: https://doi.org/10.1007/s10586-023-04080-0

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