Fuzzy Comprehensive Evaluation based NLOS Identification for UWB Indoor Positioning

Abstract. Ultra-wideband (UWB) positioning technology stands out from many indoor positioning technologies with its advantages of high precision. However, non-line-of-sight (NLOS) propagate leads to heavy range error and reduces position accuracy, this paper proposes a NLOS identification method based on channel impulse response (CIR), which includes three stages. Firstly, CIR based feature selection is carried out, which includes correlation analysis of calculated features. Secondly, fuzzy comprehensive evaluation model is introduced to NLOS identification. Finally, time of arrival (TOA) based location estimation is realized after NLOS ranging error mitigation. Simulation results show that the average identification rate of NLOS can exceed 86%, and the average positioning error can be reduced by about 0.5m.

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Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2024-10-18
DOI
https://doi.org/10.5194/isprs-annals-x-4-2024-485-2024
Citations
1
Primary Topic
Ultra-Wideband Communications Technology
Type
article
Field-Weighted Citation Impact
0.21
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Fuzzy Comprehensive Evaluation based NLOS Identification for UWB Indoor Positioning

Dongkai Yang, Jinkun Li, Chundi Xiu, M. S. Selezneva et al.
1 citations
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Ultra-Wideband Communications Technology
0.21
article

Fuzzy Comprehensive Evaluation based NLOS Identification for UWB Indoor Positioning

Dongkai Yang, Jinkun Li, Chundi Xiu, M. S. Selezneva, Feng Wang
article en
1 citations

Abstract

Abstract. Ultra-wideband (UWB) positioning technology stands out from many indoor positioning technologies with its advantages of high precision. However, non-line-of-sight (NLOS) propagate leads to heavy range error and reduces position accuracy, this paper proposes a NLOS identification method based on channel impulse response (CIR), which includes three stages. Firstly, CIR based feature selection is carried out, which includes correlation analysis of calculated features. Secondly, fuzzy comprehensive evaluation model is introduced to NLOS identification. Finally, time of arrival (TOA) based location estimation is realized after NLOS ranging error mitigation. Simulation results show that the average identification rate of NLOS can exceed 86%, and the average positioning error can be reduced by about 0.5m.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. X-4-2024
Zhejiang International Studies University (CN), Bauman Moscow State Technical University (RU), Beihang University (CN)
Climate action
Openalex Percentile: Top 47%
Ultra-Wideband Communications Technology
0.21
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