A multisensor fusion algorithm of indoor localization using derivative Euclidean distance and the weighted extended Kalman filter

Author:

Chen Jian,Song Shaojing,Gu Yang,Zhang Shanxin

Abstract

Purpose At present, smartphones are embedded with accelerometers, gyroscopes, magnetometers and WiFi sensors. Most researchers have delved into the use of these sensors for localization. However, there are still many problems in reducing fingerprint mismatching and fusing these positioning data. The purpose of this paper is to improve positioning accuracy by reducing fingerprint mismatching and designing a weighted fusion algorithm. Design/methodology/approach For the problem of magnetic mismatching caused by singularity fingerprint, derivative Euclidean distance uses adjacent fingerprints to eliminate the influence of singularity fingerprint. To improve the positioning accuracy and robustness of the indoor navigation system, a weighted extended Kalman filter uses a weighted factor to fuse multisensor data. Findings The scenes of the teaching building, study room and office building are selected to collect data to test the algorithm’s performance. Experiments show that the average positioning accuracies of the teaching building, study room and office building are 1.41 m, 1.17 m, and 1.77 m, respectively. Originality/value The algorithm proposed in this paper effectively reduces fingerprint mismatching and improve positioning accuracy by adding a weighted factor. It provides a feasible solution for indoor positioning.

Publisher

Emerald

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering

Reference40 articles.

1. Low-cost MEMS-based pedestrian navigation technique for GPS-denied areas;Journal of Sensors,2013

2. RADAR: an in-building RF-based user location and tracking system,2000

3. Indoor positioning method integrating pedestrian dead reckoning with magnetic field and WiFi fingerprints,2015

4. Localization and routing in sensor networks by local angle information;ACM Transactions on Sensor Networks,2009

5. Integrated WiFi/PDR/smartphone using an unscented Kalman filter algorithm for 3D indoor localization;Sensors,2015

Cited by 4 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