• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

一种基于超宽带测距和双气压高度计的传感器融合增强型室内三维定位系统。

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

作者信息

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

机构信息

Department of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of Korea.

Robotics Department, Hanyang University ERICA, Ansan 15588, Republic of Korea.

出版信息

Sensors (Basel). 2024 May 23;24(11):3341. doi: 10.3390/s24113341.

DOI:10.3390/s24113341
PMID:38894130
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11175163/
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.

摘要

在室内环境中进行精确的三维（3D）定位对于增强基于物品的应用服务至关重要，但当前系统在定位精度和高度估计方面常常面临困难。本研究引入了一种先进的3D定位系统，该系统集成了更新后的超宽带（UWB）传感器和双气压（BMP）传感器。利用三个固定的UWB锚点，该系统采用几何建模和卡尔曼滤波进行精确的标签3D空间定位。基于我们之前关于使用双BMP传感器进行室内高度测量的研究，所提出的系统在数据处理速度和稳定性方面有显著提升。我们的改进包括一个新的几何定位模型和一个优化的卡尔曼滤波算法，这些通过高精度运动捕捉系统进行了验证。结果表明，定位误差显著降低，高度精度约为±0.05米，3D定位系统的均方根误差（RMSE）达到0.0740米。该系统提供了更大的可定位空间和更快的数据输出速率，具有可靠的性能，可支持需要详细3D室内定位的先进应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/7c14e59a8ecb/sensors-24-03341-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/507f6333a802/sensors-24-03341-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/c39a0764f90f/sensors-24-03341-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/baeccbb76855/sensors-24-03341-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/4f575dd908ec/sensors-24-03341-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/99ccf5b69984/sensors-24-03341-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/7b69ea63255a/sensors-24-03341-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/fafb616e3e60/sensors-24-03341-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/9e430ecca59c/sensors-24-03341-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/4a15649b9347/sensors-24-03341-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/5ec0eb0d9dcf/sensors-24-03341-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/7c8dcc5e68c8/sensors-24-03341-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/6bd4150a4924/sensors-24-03341-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/e9d70057949f/sensors-24-03341-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/708a8ddb1bbf/sensors-24-03341-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/371986e0416e/sensors-24-03341-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/5fd6365a51a5/sensors-24-03341-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/a4247266bc26/sensors-24-03341-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/7c14e59a8ecb/sensors-24-03341-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/507f6333a802/sensors-24-03341-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/c39a0764f90f/sensors-24-03341-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/baeccbb76855/sensors-24-03341-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/4f575dd908ec/sensors-24-03341-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/99ccf5b69984/sensors-24-03341-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/7b69ea63255a/sensors-24-03341-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/fafb616e3e60/sensors-24-03341-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/9e430ecca59c/sensors-24-03341-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/4a15649b9347/sensors-24-03341-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/5ec0eb0d9dcf/sensors-24-03341-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/7c8dcc5e68c8/sensors-24-03341-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/6bd4150a4924/sensors-24-03341-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/e9d70057949f/sensors-24-03341-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/708a8ddb1bbf/sensors-24-03341-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/371986e0416e/sensors-24-03341-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/5fd6365a51a5/sensors-24-03341-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/a4247266bc26/sensors-24-03341-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5154/11175163/7c14e59a8ecb/sensors-24-03341-g018.jpg

相似文献

1
An Enhanced Indoor Three-Dimensional Localization System with Sensor Fusion Based on Ultra-Wideband Ranging and Dual Barometer Altimetry.一种基于超宽带测距和双气压高度计的传感器融合增强型室内三维定位系统。
Sensors (Basel). 2024 May 23;24(11):3341. doi: 10.3390/s24113341.
2
Smartphone-Based Pedestrian Dead Reckoning for 3D Indoor Positioning.基于智能手机的行人航位推算三维室内定位
Sensors (Basel). 2021 Dec 8;21(24):8180. doi: 10.3390/s21248180.
3
An Indoor Positioning Method Based on UWB and Visual Fusion.一种基于超宽带与视觉融合的室内定位方法。
Sensors (Basel). 2022 Feb 11;22(4):1394. doi: 10.3390/s22041394.
4
Comparative Analysis of Integrated Filtering Methods Using UWB Localization in Indoor Environment.室内环境中基于超宽带定位的集成滤波方法比较分析
Sensors (Basel). 2024 Feb 6;24(4):1052. doi: 10.3390/s24041052.
5
Experimental Evaluation of Sensor Fusion of Low-Cost UWB and IMU for Localization under Indoor Dynamic Testing Conditions.室内动态测试条件下低成本超宽带（UWB）与惯性测量单元（IMU）传感器融合定位的实验评估
Sensors (Basel). 2022 Oct 25;22(21):8156. doi: 10.3390/s22218156.
6
Research on a Visual/Ultra-Wideband Tightly Coupled Fusion Localization Algorithm.一种视觉/超宽带紧密耦合融合定位算法的研究
Sensors (Basel). 2024 Mar 6;24(5):1710. doi: 10.3390/s24051710.
7
A magnetometer-free indoor human localization based on loosely coupled IMU/UWB fusion.一种基于松耦合惯性测量单元/超宽带融合的无磁强计室内人体定位方法。
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:3141-4. doi: 10.1109/EMBC.2015.7319058.
8
NR-UIO: NLOS-Robust UWB-Inertial Odometry Based on Interacting Multiple Model and NLOS Factor Estimation.NR-UIO：基于交互多模型和非视距因子估计的非视距鲁棒超宽带惯性里程计
Sensors (Basel). 2021 Nov 26;21(23):7886. doi: 10.3390/s21237886.
9
Design a novel algorithm for enhancing UWB positioning accuracy in GPS denied environments.设计一种新颖的算法，用于在全球定位系统（GPS）受限环境中提高超宽带（UWB）定位精度。
Sci Rep. 2024 Oct 12;14(1):23895. doi: 10.1038/s41598-024-74773-y.
10
A Low-Cost Foot-Placed UWB and IMU Fusion-Based Indoor Pedestrian Tracking System for IoT Applications.一种基于低成本足部 UWB 和 IMU 融合的物联网应用室内行人跟踪系统。
Sensors (Basel). 2022 Oct 25;22(21):8160. doi: 10.3390/s22218160.

引用本文的文献

1
Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS.通过集成超宽带（UWB）、里程计和姿态航向参考系统（AHRS）实现移动机器人可靠定位与轨迹跟踪的多传感器融合框架
Biomimetics (Basel). 2025 Jul 21;10(7):478. doi: 10.3390/biomimetics10070478.
2
A High-Resolution Multipath Delay Measurement Method Using KFSC-WRELAX Algorithm.一种基于KFSC-WRELAX算法的高分辨率多径延迟测量方法。
Sensors (Basel). 2024 Jul 31;24(15):4968. doi: 10.3390/s24154968.

本文引用的文献

1
A Hybrid Indoor Altimetry Based on Barometer and UWB.基于气压计和超宽带的混合室内高度测量方法。
Sensors (Basel). 2023 Apr 22;23(9):4180. doi: 10.3390/s23094180.
2
A Survey of 3D Indoor Localization Systems and Technologies.三维室内定位系统与技术综述
Sensors (Basel). 2022 Dec 1;22(23):9380. doi: 10.3390/s22239380.
3
Torricelli and the ocean of air: the first measurement of barometric pressure.托里拆利与空气之海：气压的首次测量。
Physiology (Bethesda). 2013 Mar;28(2):66-73. doi: 10.1152/physiol.00053.2012.