Programmable Metasurface Antenna Assisted Indoor 2-D Positioning Using Dynamical Coding

Position estimation plays a pivotal role in indoor sensing and localization systems. However, conventional received signal strength (RSS)-based positioning methods exhibit significant limitations in both multipath interference suppression and environmental adaptability. A programmable metasurface antenna-assisted indoor 2-D positioning method integrating dynamic angle perception and a path loss model modification is proposed. This method establishes a polar coordinate system centered on the metasurface antenna, enabling simultaneous determination of the angular position and radial distance of the human in the horizontal plane. The angular detection range is from +30° to –30° with a resolution of 15°, while the radial detection range is from 0.4 m to 1.2 m. Our scheme adopts rapid metasurface beam scanning and environmental difference calculation to achieve robust angle estimation. Simultaneously, distance measurement accuracy is substantially improved by incorporating distance-dependent polynomial correction terms into the path loss model. The cumulative density function shows 80% distance estimation error for indoor environment is lower than 0.13 m in experimental validation. Compared with the traditional RSS positioning method, the proposed method has significant advantages in multipath interference suppression, environmental adaptability, response speed, algorithm complexity and deployment convenience. It has important application value in medical monitoring and robot positioning.

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Publication Details

Journal
IEEE Antennas and Wireless Propagation Letters
Published
2025-10-14
DOI
https://doi.org/10.1109/lawp.2025.3617445
Primary Topic
Antenna Design and Analysis
Type
article
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article

Programmable Metasurface Antenna Assisted Indoor 2-D Positioning Using Dynamical Coding

Jianchun Xu, Baiying Taishi, Huiming Yao, Ke Bi et al.
IEEE Antennas and Wireless Propagation Letters
Antenna Design and Analysis
article

Programmable Metasurface Antenna Assisted Indoor 2-D Positioning Using Dynamical Coding

Jianchun Xu, Baiying Taishi, Huiming Yao, Ke Bi, Bo Li, Jiaxin Li, Yang Hao
article en

Abstract

Position estimation plays a pivotal role in indoor sensing and localization systems. However, conventional received signal strength (RSS)-based positioning methods exhibit significant limitations in both multipath interference suppression and environmental adaptability. A programmable metasurface antenna-assisted indoor 2-D positioning method integrating dynamic angle perception and a path loss model modification is proposed. This method establishes a polar coordinate system centered on the metasurface antenna, enabling simultaneous determination of the angular position and radial distance of the human in the horizontal plane. The angular detection range is from +30° to –30° with a resolution of 15°, while the radial detection range is from 0.4 m to 1.2 m. Our scheme adopts rapid metasurface beam scanning and environmental difference calculation to achieve robust angle estimation. Simultaneously, distance measurement accuracy is substantially improved by incorporating distance-dependent polynomial correction terms into the path loss model. The cumulative density function shows 80% distance estimation error for indoor environment is lower than 0.13 m in experimental validation. Compared with the traditional RSS positioning method, the proposed method has significant advantages in multipath interference suppression, environmental adaptability, response speed, algorithm complexity and deployment convenience. It has important application value in medical monitoring and robot positioning.

IEEE Antennas and Wireless Propagation LettersVol. 24(12)
Beijing University of Posts and Telecommunications (CN)
Openalex Percentile: Top 61%
Antenna Design and Analysis
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Programmable Metasurface Antenna Assisted Indoor 2-D Positioning Using Dynamical Coding — Jianchun Xu, Baiying Taishi, et al. · IEEE Antennas and Wireless Propagation Letters (2025) | TGRS Research Map | TGRS