Map-assisted UWB/INS tight combination for indoor localization

A map-assisted ultra-wide band (UWB)/inertial navigation system (INS) tight combination localization method is proposed to address the degradation of localization accuracy of indoor ultra-wide band localization system due to the obstruction of the signal propagation path under the non-line-of-sight (NLOS) propagation environment. The map database is established by the spatial data information in the indoor construction engineering drawings, and the two-step algorithm of recognizing the non-line-of-sight distance is adopted firstly for coarse recognition and then for fine recognition, and the error correction is carried out by using the error state Kalman filter fusion of UWB/INS to further correct the cumulative error of INS. The experimental results show that the planar positioning accuracy of the algorithm proposed in this paper is within 0.35m, which improves the positioning accuracy by 72.5% compared to the tight combination of UWB/INS positioning method without NLOS identification.

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Publication Details

Published
2025-09-29
DOI
https://doi.org/10.1117/12.3082969
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
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article

Map-assisted UWB/INS tight combination for indoor localization

Zeqi Song, Jianhua Cheng
Indoor and Outdoor Localization Technologies
article

Map-assisted UWB/INS tight combination for indoor localization

Zeqi Song, Jianhua Cheng
article en

Abstract

A map-assisted ultra-wide band (UWB)/inertial navigation system (INS) tight combination localization method is proposed to address the degradation of localization accuracy of indoor ultra-wide band localization system due to the obstruction of the signal propagation path under the non-line-of-sight (NLOS) propagation environment. The map database is established by the spatial data information in the indoor construction engineering drawings, and the two-step algorithm of recognizing the non-line-of-sight distance is adopted firstly for coarse recognition and then for fine recognition, and the error correction is carried out by using the error state Kalman filter fusion of UWB/INS to further correct the cumulative error of INS. The experimental results show that the planar positioning accuracy of the algorithm proposed in this paper is within 0.35m, which improves the positioning accuracy by 72.5% compared to the tight combination of UWB/INS positioning method without NLOS identification.

Harbin Engineering University (CN)
Openalex Percentile: Top 74%
Indoor and Outdoor Localization Technologies
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