Evidence map›Paper›PMID 38894130›Full record

ArticleSensors (Basel, Switzerland)2024

An Enhanced Indoor Three-Dimensional Localization System with Sensor Fusion Based on Ultra-Wideband Ranging and Dual Barometer Altimetry.

Le Bao, Kai Li, Joosun Lee, Wenbin Dong, Wenqi Li, Kyoosik Shin, Wansoo Kim

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Le BaoDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of Korea.ORCID 0000-0001-5284-473X
Kai LiDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of Korea.ORCID 0000-0002-2027-1153
Joosun LeeDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of Korea.ORCID 0000-0001-7489-0833
Wenbin DongDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of Korea.ORCID 0009-0004-2485-127X
Wenqi LiDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of Korea.ORCID 0009-0003-8520-9582
Kyoosik ShinRobotics Department, Hanyang University ERICA, Ansan 15588, Republic of Korea.
Wansoo KimRobotics Department, Hanyang University ERICA, Ansan 15588, Republic of Korea.ORCID 0000-0002-3254-3929

Funding

China Scholarship Council(CSC) 202108260014National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) 2022R1C1C1008306
6 · The paper itself

Abstract

Accurate three-dimensional (3D) localization within indoor environments is crucial for enhancing item-based application services, yet current systems often struggle with localization accuracy and height estimation. This study introduces an advanced 3D localization system that integrates updated ultra-wideband (UWB) sensors and dual barometric pressure (BMP) sensors. Utilizing three fixed UWB anchors, the system employs geometric modeling and Kalman filtering for precise tag 3D spatial localization. Building on our previous research on indoor height measurement with dual BMP sensors, the proposed system demonstrates significant improvements in data processing speed and stability. Our enhancements include a new geometric localization model and an optimized Kalman filtering algorithm, which are validated by a high-precision motion capture system. The results show that the localization error is significantly reduced, with height accuracy of approximately ±0.05 m, and the Root Mean Square Error (RMSE) of the 3D localization system reaches 0.0740 m. The system offers expanded locatable space and faster data output rates, delivering reliable performance that supports advanced applications requiring detailed 3D indoor localization.

Indexed as

barometric pressure sensorindoor localizationKalman filterultra-wideband sensor

Identifiers

PMID38894130
PMCPMC11175163

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.