Accuracy Improvement of Indoor Real-Time Location Tracking Algorithm for Smart Supermarket Based on Ultra-Wideband

Author:

Hu Guohua1ORCID,Feldhaus Pascal2,Feng Yuwu1,Wang Shengjie1,Zheng Juan1,Duan Huimin1,Gu Juanjuan1

Affiliation:

1. Department of Electronic Information and Electric Engineering, Hefei University, Hefei, Anhui 230601, P. R. China

2. Department of Electrical Engineering and Computer Science, Stralsund University of Applied Sciences, D-18435 Stralsund, Germany

Abstract

Collecting data like location information is an essential part of concepts like the “IoT” or “Industry 4.0”. In the case of the development of a precise localization system and an integrated navigation system, indoor location technology receives more and more attention and has become a hot research topic. Common indoor location techniques are mainly based on wireless local area network, radio frequency tag, ZigBee technology, Bluetooth technology, infrared technology and ultra-wideband (UWB). However, these techniques are vulnerable to various noise signals and indoor environments, and also the positioning accuracy is easily affected by the complicated indoor environment. We studied the problem of real-time location tracking based on UWB in an indoor environment in this paper. We have proposed a combinational filtering algorithm and an improved Two-Way Ranging (ITWR) method for indoor real-time location tracking. The simulation results prove that the real-time performance and high accuracy of the presented algorithm can improve location accuracy. The experiment shows that the combinational algorithm and ITWR method which are applied to the positioning and navigation of the smart supermarket, have achieved quiet good results in positioning accuracy. The average positioning error is less than 10[Formula: see text]cm, some of the improvements can elevate the positioning accuracy by 17.5%. UWB is a suitable method for indoor real-time location tracking and has important theoretic value and practical significance.

Funder

Natural Science Foundation of Anhui Provincial Education Department

Quality Engineering Project of Anhui Province

Key Discipline Construction Project of Hefei University

Research and Development Fund Project of Hefei University

Academic Subsidy Project

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3