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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.

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/7663842/396e897f2e04/sensors-20-06292-g001.jpg

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