Scanning method for indoor localization using the RSSI approach

Author:

Warda Ahmad,Petković Bojana,Toepfer HannesORCID

Abstract

Abstract. This paper presents a scanning method for indoor mobile robot localization using the received signal strength indicator (RSSI) approach. The method eliminates the main drawback of the conventional fingerprint, whose database construction is time-consuming and which needs to be rebuilt every time a change in indoor environment occurs. It directly compares the column vectors of a kernel matrix and signal strength vector using the Euclidean distance as a metric. The highest resolution available in localization using a fingerprint is restricted by a resolution of a set of measurements performed prior to localization. In contrast, resolution using the scanning method can be easily changed using a denser grid of potential sources. Although slightly slower than the trilateration method, the scanning method outperforms it in terms of accuracy, and yields a reconstruction error of only 0. 08 m averaged over 1600 considered source points in a room with dimensions 9.7 m × 4.7 m × 3 m. Its localization time of 0. 39 s makes this method suitable for real-time localization and tracking.

Publisher

Copernicus GmbH

Subject

Electrical and Electronic Engineering,Instrumentation

Cited by 3 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

1. K-Ranking RSSI Vectors Cosine Value Localization Method for Indoor Positioning;2022 10th International Conference on Agro-geoinformatics (Agro-Geoinformatics);2022-07-11

2. WiCLoc: A Novel CSI-based Fingerprint Localization System;International Journal of Pattern Recognition and Artificial Intelligence;2019-08-09

3. Indoor localization: novel RSSI approach based on analytical solution and two receivers;Journal of Sensors and Sensor Systems;2017-11-20

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