Non-line-of-sight ultra-wideband signal recognition using DWT-CNN

Jianguo He; Wentao Zhao; Yiru Liu; Fengqing Han

doi:10.1117/12.3029155

6 May 2024 Non-line-of-sight ultra-wideband signal recognition using DWT-CNN

Jianguo He, Wentao Zhao, Yiru Liu, Fengqing Han

Proceedings Volume 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024); 131072I (2024) https://doi.org/10.1117/12.3029155
Event: Fourth International Conference on Sensors and Information Technology (ICSI 2024), 2024, Xiamen, China

Abstract

With the development of technology, the application of positioning techniques has become increasingly widespread. However, in indoor or specific situations, due to the complexity of the environment, it can be challenging to apply outdoor positioning techniques. Therefore, research on indoor positioning techniques is highly necessary. Ultra-Wideband (UWB) technology, as an indoor positioning method, can address many indoor positioning scenarios. However, when facing obstacles, it can still lead to non-line-of-sight (NLOS) situations, resulting in less accurate positioning. To address this issue, this paper proposes an approach that combines Discrete Wavelet Transform (DWT) and Convolutional Neural Networks (CNN). Firstly, it extracts coefficients from Channel Impulse Response (CIR) signals using DWT. Subsequently, these coefficients are input to a CNN to explore deep features, ultimately distinguishing between Non-Line-of-Sight (NLOS) and Line-of-Sight (LOS) signals based on these features. Experimental results demonstrate that this method achieves better classification accuracy compared to other approaches.

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

Citation Download Citation

Jianguo He, Wentao Zhao, Yiru Liu, and Fengqing Han "Non-line-of-sight ultra-wideband signal recognition using DWT-CNN", Proc. SPIE 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024), 131072I (6 May 2024); https://doi.org/10.1117/12.3029155

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