Research on optimized deployment methods for indoor UWB base stations based on three-dimensional spatial analysis

Dexu Zou; Xiangwei Zhao; Lixing Zhang; Haoquan Ma; Xianghui Kong

doi:10.1117/12.3007524

30 August 2023 Research on optimized deployment methods for indoor UWB base stations based on three-dimensional spatial analysis

Dexu Zou, Xiangwei Zhao, Lixing Zhang, Haoquan Ma, Xianghui Kong

Author Affiliations +

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127972I (2023) https://doi.org/10.1117/12.3007524
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

Ultra-wideband (UWB) positioning technology is prone to be obscured by various objects in indoor complex environments and generates non-line-of-sight errors (NLOS). In view of the current situation that there are few studies on how to deploy UWB in indoor complex environments to ensure positioning accuracy while minimizing the use of UWB base stations and saving costs, this study generates positioning ranges based on AGV tracking routes; divides positioning ranges based on UWB positioning ranges to generate basic UWB deployment points; analyzes blind areas of UWB signals through threedimensional spatial analysis technology; encrypts and deploys UWB base stations for blind areas; and analyzes the rationality of dense deployment points through three-dimensional spatial analysis technology. Finally, through simulation experiment, a scientific and reasonable base station deployment process is provided for UWB deployment in indoor complex environment.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dexu Zou, Xiangwei Zhao, Lixing Zhang, Haoquan Ma, and Xianghui Kong "Research on optimized deployment methods for indoor UWB base stations based on three-dimensional spatial analysis", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127972I (30 August 2023); https://doi.org/10.1117/12.3007524

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