• 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

松耦合 GNSS 和 UWB 与 INS 集成的室内/室外行人导航。

Loosely Coupled GNSS and UWB with INS Integration for Indoor/Outdoor Pedestrian Navigation.

机构信息

Department of Environment Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.

Politecnico di Torino Interdepartmental Centre for Service Robotics (PIC4SeR), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.

出版信息

Sensors (Basel). 2020 Nov 5;20(21):6292. doi: 10.3390/s20216292.

DOI:10.3390/s20216292
PMID:33167359
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7663842/
Abstract

The growth of location-based services (LBS) has increased rapidly in last years, mainly due to the possibility to exploit low-cost sensors installed in portable devices, such as smartphones and tablets. This work aims to show a low-cost multi-sensor platform developed by the authors in which an ultra-wideband (UWB) indoor positioning system is added to a classical global navigation satellite systems-inertial navigation system (GNSS-INS) integration, in order to acquire different synchronized data for further data fusion analysis in order to exploit seamless positioning. The data fusion is based on an extended Kalman filter (EKF) and on a geo-fencing approach which allows the navigation solution to be provided continuously. In particular, the proposed algorithm aims to solve a navigation task of a pedestrian user moving from an outdoor space to an indoor environment. The methodology and the system setup is presented with more details in the paper. The data acquired and the real-time positioning estimation are analysed in depth and compared with ground truth measurements. Particular attention is given to the UWB positioning system and its behaviour with respect to the environment. The proposed data fusion algorithm provides an overall horizontal and 3D accuracy of 35 cm and 45 cm, respectively, obtained considering 5 different measurement campaigns.

摘要

近年来，基于位置的服务（LBS）的发展迅速增长，主要得益于能够利用便携式设备（如智能手机和平板电脑）中安装的低成本传感器。本工作旨在展示作者开发的低成本多传感器平台，其中添加了超宽带（UWB）室内定位系统到经典的全球导航卫星系统-惯性导航系统（GNSS-INS）集成中，以获取不同的同步数据，以便进一步进行数据融合分析，从而实现无缝定位。数据融合基于扩展卡尔曼滤波器（EKF）和地理围栏方法，允许连续提供导航解决方案。具体来说，所提出的算法旨在解决行人用户从室外空间移动到室内环境的导航任务。该方法和系统设置在论文中有更详细的介绍。对所采集的数据和实时定位估计进行了深入分析，并与地面真实测量值进行了比较。特别关注 UWB 定位系统及其在环境中的行为。所提出的数据融合算法分别考虑了 5 次不同的测量活动，提供了整体水平和 3D 精度分别为 35cm 和 45cm。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/78cc10cceeec/sensors-20-06292-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/396e897f2e04/sensors-20-06292-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/b2395bda82f8/sensors-20-06292-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/89d8c88da60c/sensors-20-06292-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/fb06e5a3b3b9/sensors-20-06292-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/07fb4a1c2179/sensors-20-06292-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/8fe19d666703/sensors-20-06292-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/76ed72ffdbcd/sensors-20-06292-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/b926114072fb/sensors-20-06292-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/64911b6b6760/sensors-20-06292-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/1b81755b5ab4/sensors-20-06292-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/78cc10cceeec/sensors-20-06292-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/396e897f2e04/sensors-20-06292-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/b2395bda82f8/sensors-20-06292-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/89d8c88da60c/sensors-20-06292-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/fb06e5a3b3b9/sensors-20-06292-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/07fb4a1c2179/sensors-20-06292-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/8fe19d666703/sensors-20-06292-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/76ed72ffdbcd/sensors-20-06292-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/b926114072fb/sensors-20-06292-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/64911b6b6760/sensors-20-06292-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/1b81755b5ab4/sensors-20-06292-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b0d/7663842/78cc10cceeec/sensors-20-06292-g011.jpg

相似文献

1
Loosely Coupled GNSS and UWB with INS Integration for Indoor/Outdoor Pedestrian Navigation.松耦合 GNSS 和 UWB 与 INS 集成的室内/室外行人导航。
Sensors (Basel). 2020 Nov 5;20(21):6292. doi: 10.3390/s20216292.
2
An Emergency Seamless Positioning Technique Based on ad hoc UWB Networking Using Robust EKF.一种基于使用鲁棒扩展卡尔曼滤波器的自组织超宽带网络的应急无缝定位技术。
Sensors (Basel). 2019 Jul 16;19(14):3135. doi: 10.3390/s19143135.
3
A UWB/Improved PDR Integration Algorithm Applied to Dynamic Indoor Positioning for Pedestrians.一种应用于行人动态室内定位的 UWB/改进 PDR 集成算法。
Sensors (Basel). 2017 Sep 8;17(9):2065. doi: 10.3390/s17092065.
4
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.
5
An INS and UWB Fusion-Based Gyroscope Drift Correction Approach for Indoor Pedestrian Tracking.基于 INS 和 UWB 融合的室内行人跟踪用陀螺仪漂移校正方法。
Sensors (Basel). 2020 Aug 10;20(16):4476. doi: 10.3390/s20164476.
6
Robustly Adaptive EKF PDR/UWB Integrated Navigation Based on Additional Heading Constraint.基于附加航向约束的鲁棒自适应扩展卡尔曼滤波航位推算/超宽带集成导航
Sensors (Basel). 2021 Jun 26;21(13):4390. doi: 10.3390/s21134390.
7
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.
8
Decimeter-Level Accuracy for Smartphone Real-Time Kinematic Positioning Implementing a Robust Kalman Filter Approach and Inertial Navigation System Infusion in Complex Urban Environments.通过在复杂城市环境中采用稳健卡尔曼滤波方法和融合惯性导航系统，实现智能手机实时动态定位的分米级精度。
Sensors (Basel). 2024 Sep 11;24(18):5907. doi: 10.3390/s24185907.
9
Fusion of GNSS Pseudoranges with UWB Ranges Based on Clustering and Weighted Least Squares.基于聚类和加权最小二乘法的 GNSS 伪距与 UWB 距离融合。
Sensors (Basel). 2023 Mar 21;23(6):3303. doi: 10.3390/s23063303.
10
Enhanced Autonomous Vehicle Positioning Using a Loosely Coupled INS/GNSS-Based Invariant-EKF Integration.利用基于松散耦合 INS/GNSS 的不变量扩展卡尔曼滤波集成实现增强型自动驾驶车辆定位。
Sensors (Basel). 2023 Jul 2;23(13):6097. doi: 10.3390/s23136097.

引用本文的文献

1
Comprehensive outdoor UWB dataset: Static and dynamic measurements in LOS/NLOS environments.综合户外超宽带数据集：视距/非视距环境中的静态和动态测量
Sci Data. 2025 Sep 2;12(1):1532. doi: 10.1038/s41597-025-05887-9.
2
A Combined UWB/IMU Localization Method with Improved CKF.一种采用改进型无迹卡尔曼滤波器的超宽带/惯性测量单元组合定位方法。
Sensors (Basel). 2024 May 16;24(10):3165. doi: 10.3390/s24103165.
3
Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs.自主无人机中通过DDS网络连接的低资源设备的延迟降低与数据包同步

本文引用的文献

1
Automatic Calibration of the Step Length Model of a Pocket INS by Means of a Foot Inertial Sensor.利用足部惯性传感器实现口袋 INS 步长模型的自动校准。
Sensors (Basel). 2020 Apr 7;20(7):2083. doi: 10.3390/s20072083.
2
Environmental Cross-Validation of NLOS Machine Learning Classification/Mitigation with Low-Cost UWB Positioning Systems.环境下的非视距机器学习分类/缓解与低成本超宽带定位系统的交叉验证。
Sensors (Basel). 2019 Dec 10;19(24):5438. doi: 10.3390/s19245438.
3
Single-Baseline RTK Positioning Using Dual-Frequency GNSS Receivers Inside Smartphones.
Sensors (Basel). 2023 Nov 18;23(22):9269. doi: 10.3390/s23229269.
4
The Design of GNSS/IMU Loosely-Coupled Integration Filter for Wearable EPTS of Football Players.足球运动员可穿戴式 EPTS 的 GNSS/IMU 松组合集成滤波器设计。
Sensors (Basel). 2023 Feb 4;23(4):1749. doi: 10.3390/s23041749.
5
Indoor Positioning System with UWB Based on a Digital Twin.基于数字孪生的超宽带室内定位系统。
Sensors (Basel). 2022 Aug 9;22(16):5936. doi: 10.3390/s22165936.
6
Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection.建筑检测的无缝导航、3D 重建、热成像和语义绘图。
Sensors (Basel). 2022 Jun 23;22(13):4745. doi: 10.3390/s22134745.
7
Toward Accurate Indoor Positioning: An RSS-Based Fusion of UWB and Machine-Learning-Enhanced WiFi.迈向精确室内定位：基于接收信号强度的超宽带与机器学习增强型WiFi融合技术
Sensors (Basel). 2022 Apr 21;22(9):3204. doi: 10.3390/s22093204.
8
Multi-GNSS Precise Point Positioning with UWB Tightly Coupled Integration.基于超宽带紧密耦合集成的多全球导航卫星系统精密单点定位
Sensors (Basel). 2022 Mar 14;22(6):2232. doi: 10.3390/s22062232.
9
Improving the Accuracy of Decawave's UWB MDEK1001 Location System by Gaining Access to Multiple Ranges.通过获取多个范围来提高 Decawave 的 UWB MDEK1001 定位系统的精度。
Sensors (Basel). 2021 Mar 4;21(5):1787. doi: 10.3390/s21051787.
智能手机中利用双频 GNSS 接收机进行单基线 RTK 定位。
Sensors (Basel). 2019 Oct 4;19(19):4302. doi: 10.3390/s19194302.
4
Analysis of the Scalability of UWB Indoor Localization Solutions for High User Densities.分析超高带宽室内定位解决方案在高密度用户环境下的可扩展性。
Sensors (Basel). 2018 Jun 7;18(6):1875. doi: 10.3390/s18061875.
5
Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances.超宽带室内定位技术：分析与最新进展
Sensors (Basel). 2016 May 16;16(5):707. doi: 10.3390/s16050707.