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.
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