Indoor dynamic object positioning in NLOS environment based on UWB

HE Yongping; LIU Ran; FU Wenpeng; LIANG Gaoli; FU Yulu; ZHANG Hua

doi:10.13873/J.1000-9787(2020)08-0046-04

Chinese

您当前的位置：

首页 >

文章列表页 >

Indoor dynamic object positioning in NLOS environment based on UWB

更新时间：2025-09-11

- Indoor dynamic object positioning in NLOS environment based on UWB
- Issue 8, Pages: 46-49+54(2020)
- 作者机构：
  
  西南科技大学信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2020)08-0046-04
  CLC： TN925
- Published：2020
- 稿件说明：
移动端阅览
HE Yongping, LIU Ran, FU Wenpeng, et al. Indoor dynamic object positioning in NLOS environment based on UWB[J]. 2020, (8): 46-49+54.
DOI：

HE Yongping, LIU Ran, FU Wenpeng, et al. Indoor dynamic object positioning in NLOS environment based on UWB[J]. 2020, (8): 46-49+54. DOI： 10.13873/J.1000-9787(2020)08-0046-04.

摘要

针对超宽带(UWB)定位技术受到环境中非视距(NLOS)因素的影响

造成定位精度低、定位稳定性差的问题

提出对UWB采集的原始数据进行两次粒子滤波

从而实现精准的动态目标定位。第一次粒子滤波算法用于存储每个锚点测量距离与误差关系模型。第二次粒子滤波在更新阶段根据距离误差模型调节权重

进一步约束估计的目标粒子

实现更精准的动态目标定位。不同环境下的实验结果表明:该算法能有效抑制NLOS误差的影响

在非视距严重的环境中定位精度能达到0.29 m

相比于系统提供的三边测量定位算法精度提高48.21%

相比传统粒子滤波精度提高17.14%

明显提高了NLOS传播环境下的动态目标定位精度。

Abstract

Aiming at the problem that ultra wide band（ UWB） positioning technology is highly impacted by nonline of sight（ NLOS） factors from an environment

which results in low positioning precision and poor positioning stability

an approach is proposed for accurate dynamic target positioning by applying particle filtering twice on the raw data collected by the UWB. The first particle filtering is used to save the relational model between the measured distance and the error model of each anchor. Based on the model

the second particle filter is used by assigning particles with different weights to improve the positioning accuracy. Experimental results in different environments show that the proposed algorithm can effectively suppress the influence of NLOS error. With this algorithm implemented

the positioning accuracy of the dynamic object reaches 0. 29 m at the moment when NLOS errors appear to be serious

which is an improvement of 48. 21 % and 17. 14 % when compared with the triangulation algorithm provided by the UWB system and traditional particle filtering-based approach. The dynamic object positioning accuracy is remarkably improved in NLOS environment.

关键词

Keywords

references

Views

618

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Indoor positioning method based on multi-source information fusion

A UWB positioning method for suppressing NLOS error

Combined VLC and PDR indoor positioning method based on factor graph

Barometer-assisted UWB indoor positioning method

Multi-directional grouping WiFi indoor positioning algorithm

Related Author

HAN Leng

DAI Peng

YANG Yuan

WANG Qing

BAO Xiaoyu

WANG Qing

YANG Yuan

CHENG Xianghong

Related Institution

School of Instrument Science and Engineering, Southeast University

College of Computer Science & Technology,Henan Polytechnic University

National Astronomical Observatories of Chinese Academy of Sciences

School of Communication Engineering,Hangzhou Dianzi University

School of Electrical Engineering ＆ Automation,Henan Polytechnic University

⁰