BLE-Based Indoor Localization: Analysis of Some Solutions for Performance Improvement

Author:

Milano Filippo1ORCID,da Rocha Helbert23ORCID,Laracca Marco4ORCID,Ferrigno Luigi1ORCID,Espírito Santo António23ORCID,Salvado José23ORCID,Paciello Vincenzo5ORCID

Affiliation:

1. Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy

2. Department of Electromechanical Engineering, University of Beira Interior, 6200-001 Covilhã, Portugal

3. Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal

4. Department of Astronautics, Electrical and Energy Engineering, Sapienza University of Rome, 00185 Rome, Italy

5. Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy

Abstract

This paper addresses indoor localization using an anchor-based system based on Bluetooth Low Energy (BLE) 5.0 technology, adopting the Received Signal Strength Indicator (RSSI) for the distance estimation. Different solutions have been proposed in the scientific literature to improve the performance of this localization technology, but a detailed performance comparison of these solutions is still missing. The aim of this work is to make an experimental analysis combining different solutions for the performance improvement of BLE-based indoor localization, identifying the most effective one. The considered solutions involve different RSSI signals’ conditioning, the use of anchor–tag distance estimation techniques, as well as approaches for estimating the unknown tag position. An experimental campaign was executed in a complex indoor environment, characterized by the continuous presence in the movement of working staff and numerous obstacles. The exploitation of multichannel transmission using RSSI signal aggregation techniques showed the greater performance improvement of the localization system, reducing the positioning error (from 1.5 m to about 1 m). The other examined solutions have shown a lesser impact in the performance improvement with a decrease or an increase in the positioning errors, depending on the considered combination of the adopted solutions.

Funder

Project GreenAuto: Green Innovation for the Automotive Industry

Recovery and Resilience Plan and by European Funds NextGenerationEU

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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