High-Precision Multipath-Based Indoor Localization Scheme With User Privacy Protection for Dynamic NLoS Environments
High-precision indoor localization systems (ILSs) are critical for applications such as human smartphone navigation, autonomous robotics and automated warehouse and factory design. This paper presents a novel fingerprinting-based ILS, which features a decimeter-level localization accuracy, the abili...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9512092/ |
id |
doaj-6593330400a240a481dedcd259ec847c |
---|---|
record_format |
Article |
spelling |
doaj-6593330400a240a481dedcd259ec847c2021-08-26T23:00:30ZengIEEEIEEE Access2169-35362021-01-01911603311604910.1109/ACCESS.2021.31043319512092High-Precision Multipath-Based Indoor Localization Scheme With User Privacy Protection for Dynamic NLoS EnvironmentsAlexandra Zayets0https://orcid.org/0000-0001-9129-6406Christian Gentner1https://orcid.org/0000-0003-4298-8195Eckehard Steinbach2https://orcid.org/0000-0001-8853-2703Chair of Media Technology, Technical University of Munich, Munich, GermanyGerman Aerospace Center, Institute of Communications and Navigation, Oberpfaffenhofen, Wessling, GermanyChair of Media Technology, Technical University of Munich, Munich, GermanyHigh-precision indoor localization systems (ILSs) are critical for applications such as human smartphone navigation, autonomous robotics and automated warehouse and factory design. This paper presents a novel fingerprinting-based ILS, which features a decimeter-level localization accuracy, the ability to function in a constantly changing non line-of-sight (NLoS) environment, and user privacy protection without the need for heavy computations. The proposed ILS is able to maintain its localization accuracy in a constantly changing environment and to camouflage the user’s location by leveraging multipath propagation. The method was successfully tested both by experimental verification using the ultra-wideband communication standard and a ray-tracing simulation. An average localization error of 6 cm is demonstrated for a stationary or slow-moving receiver. An average error of 30 cm is demonstrated for a receiver that is moving at a fast walking pace. The obtained localization accuracy is comparable to the accuracy of the state-of-the-art localization algorithms. At the same time, the proposed approach solves two practical challenges faced by ILSs: robustness to changing environments with moving objects and the high computation requirements of user privacy protection. The high degree of user privacy was evaluated using a set of corresponding metrics.https://ieeexplore.ieee.org/document/9512092/Indoor localizationmultipath fingerprintingcamouflage-based privacy protection |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alexandra Zayets Christian Gentner Eckehard Steinbach |
spellingShingle |
Alexandra Zayets Christian Gentner Eckehard Steinbach High-Precision Multipath-Based Indoor Localization Scheme With User Privacy Protection for Dynamic NLoS Environments IEEE Access Indoor localization multipath fingerprinting camouflage-based privacy protection |
author_facet |
Alexandra Zayets Christian Gentner Eckehard Steinbach |
author_sort |
Alexandra Zayets |
title |
High-Precision Multipath-Based Indoor Localization Scheme With User Privacy Protection for Dynamic NLoS Environments |
title_short |
High-Precision Multipath-Based Indoor Localization Scheme With User Privacy Protection for Dynamic NLoS Environments |
title_full |
High-Precision Multipath-Based Indoor Localization Scheme With User Privacy Protection for Dynamic NLoS Environments |
title_fullStr |
High-Precision Multipath-Based Indoor Localization Scheme With User Privacy Protection for Dynamic NLoS Environments |
title_full_unstemmed |
High-Precision Multipath-Based Indoor Localization Scheme With User Privacy Protection for Dynamic NLoS Environments |
title_sort |
high-precision multipath-based indoor localization scheme with user privacy protection for dynamic nlos environments |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
High-precision indoor localization systems (ILSs) are critical for applications such as human smartphone navigation, autonomous robotics and automated warehouse and factory design. This paper presents a novel fingerprinting-based ILS, which features a decimeter-level localization accuracy, the ability to function in a constantly changing non line-of-sight (NLoS) environment, and user privacy protection without the need for heavy computations. The proposed ILS is able to maintain its localization accuracy in a constantly changing environment and to camouflage the user’s location by leveraging multipath propagation. The method was successfully tested both by experimental verification using the ultra-wideband communication standard and a ray-tracing simulation. An average localization error of 6 cm is demonstrated for a stationary or slow-moving receiver. An average error of 30 cm is demonstrated for a receiver that is moving at a fast walking pace. The obtained localization accuracy is comparable to the accuracy of the state-of-the-art localization algorithms. At the same time, the proposed approach solves two practical challenges faced by ILSs: robustness to changing environments with moving objects and the high computation requirements of user privacy protection. The high degree of user privacy was evaluated using a set of corresponding metrics. |
topic |
Indoor localization multipath fingerprinting camouflage-based privacy protection |
url |
https://ieeexplore.ieee.org/document/9512092/ |
work_keys_str_mv |
AT alexandrazayets highprecisionmultipathbasedindoorlocalizationschemewithuserprivacyprotectionfordynamicnlosenvironments AT christiangentner highprecisionmultipathbasedindoorlocalizationschemewithuserprivacyprotectionfordynamicnlosenvironments AT eckehardsteinbach highprecisionmultipathbasedindoorlocalizationschemewithuserprivacyprotectionfordynamicnlosenvironments |
_version_ |
1721189132335579136 |