Cargando…

The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks

Indoor localization is a significant research area in wireless sensor networks (WSNs). Generally, the nodes of WSNs are deployed in the same plane, i.e., the floor, as the target to be positioned, which causes the sensing signal to be influenced or even blocked by unpredictable obstacles, like furni...

Descripción completa

Detalles Bibliográficos
Autores principales: Jia, Zixi, Wu, Chengdong, Li, Zhao, Zhang, Yunzhou, Guan, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4701353/
https://www.ncbi.nlm.nih.gov/pubmed/26610518
http://dx.doi.org/10.3390/s151129661
_version_ 1782408468051787776
author Jia, Zixi
Wu, Chengdong
Li, Zhao
Zhang, Yunzhou
Guan, Bo
author_facet Jia, Zixi
Wu, Chengdong
Li, Zhao
Zhang, Yunzhou
Guan, Bo
author_sort Jia, Zixi
collection PubMed
description Indoor localization is a significant research area in wireless sensor networks (WSNs). Generally, the nodes of WSNs are deployed in the same plane, i.e., the floor, as the target to be positioned, which causes the sensing signal to be influenced or even blocked by unpredictable obstacles, like furniture. However, a 3D system, like Cricket, can reduce the negative impact of obstacles to the maximum extent and guarantee the sensing signal transmission by using the line of sight (LOS). However, most of the traditional localization methods are not available for the new deployment mode. In this paper, we propose the self-localization of beacons method based on the Cayley–Menger determinant, which can determine the positions of beacons stuck in the ceiling; and differential sensitivity analysis (DSA) is also applied to eliminate measurement errors in measurement data fusion. Then, the calibration of beacons scheme is proposed to further refine the locations of beacons by the mobile robot. According to the robot’s motion model based on dead reckoning, which is the process of determining one’s current position, we employ the [Formula: see text] filter and the strong tracking filter (STF) to calibrate the rough locations, respectively. Lastly, the optimal node selection scheme based on geometric dilution precision (GDOP) is presented here, which is able to pick the group of beacons with the minimum GDOP from all of the beacons. Then, we propose the GDOP-based weighting estimation method (GWEM) to associate redundant information with the position of the target. To verify the proposed methods in the paper, we design and conduct a simulation and an experiment in an indoor setting. Compared to EKF and the [Formula: see text] filter, the adopted STF method can more effectively calibrate the locations of beacons; GWEM can provide centimeter-level precision in 3D environments by using the combination of beacons that minimizes GDOP.
format Online
Article
Text
id pubmed-4701353
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-47013532016-01-19 The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks Jia, Zixi Wu, Chengdong Li, Zhao Zhang, Yunzhou Guan, Bo Sensors (Basel) Article Indoor localization is a significant research area in wireless sensor networks (WSNs). Generally, the nodes of WSNs are deployed in the same plane, i.e., the floor, as the target to be positioned, which causes the sensing signal to be influenced or even blocked by unpredictable obstacles, like furniture. However, a 3D system, like Cricket, can reduce the negative impact of obstacles to the maximum extent and guarantee the sensing signal transmission by using the line of sight (LOS). However, most of the traditional localization methods are not available for the new deployment mode. In this paper, we propose the self-localization of beacons method based on the Cayley–Menger determinant, which can determine the positions of beacons stuck in the ceiling; and differential sensitivity analysis (DSA) is also applied to eliminate measurement errors in measurement data fusion. Then, the calibration of beacons scheme is proposed to further refine the locations of beacons by the mobile robot. According to the robot’s motion model based on dead reckoning, which is the process of determining one’s current position, we employ the [Formula: see text] filter and the strong tracking filter (STF) to calibrate the rough locations, respectively. Lastly, the optimal node selection scheme based on geometric dilution precision (GDOP) is presented here, which is able to pick the group of beacons with the minimum GDOP from all of the beacons. Then, we propose the GDOP-based weighting estimation method (GWEM) to associate redundant information with the position of the target. To verify the proposed methods in the paper, we design and conduct a simulation and an experiment in an indoor setting. Compared to EKF and the [Formula: see text] filter, the adopted STF method can more effectively calibrate the locations of beacons; GWEM can provide centimeter-level precision in 3D environments by using the combination of beacons that minimizes GDOP. MDPI 2015-11-24 /pmc/articles/PMC4701353/ /pubmed/26610518 http://dx.doi.org/10.3390/s151129661 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jia, Zixi
Wu, Chengdong
Li, Zhao
Zhang, Yunzhou
Guan, Bo
The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks
title The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks
title_full The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks
title_fullStr The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks
title_full_unstemmed The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks
title_short The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks
title_sort indoor localization and tracking estimation method of mobile targets in three-dimensional wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4701353/
https://www.ncbi.nlm.nih.gov/pubmed/26610518
http://dx.doi.org/10.3390/s151129661
work_keys_str_mv AT jiazixi theindoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT wuchengdong theindoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT lizhao theindoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT zhangyunzhou theindoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT guanbo theindoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT jiazixi indoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT wuchengdong indoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT lizhao indoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT zhangyunzhou indoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks
AT guanbo indoorlocalizationandtrackingestimationmethodofmobiletargetsinthreedimensionalwirelesssensornetworks