Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter Estimation

In wireless sensor network (WSN)-based rigid body localization (RBL) systems, the non-line-of-sight (NLOS) propagation of the wireless signals leads to severe performance deterioration. This paper focuses on the RBL problem under the NLOS environment based on the time of arrival (TOA) measurement be...

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Main Authors: Pengwu Wan, Jian Wei, Jin Wang, Qiongdan Huang
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/22/18/6810
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author Pengwu Wan
Jian Wei
Jin Wang
Qiongdan Huang
author_facet Pengwu Wan
Jian Wei
Jin Wang
Qiongdan Huang
author_sort Pengwu Wan
collection DOAJ
description In wireless sensor network (WSN)-based rigid body localization (RBL) systems, the non-line-of-sight (NLOS) propagation of the wireless signals leads to severe performance deterioration. This paper focuses on the RBL problem under the NLOS environment based on the time of arrival (TOA) measurement between the sensors fixed on the rigid body and the anchors, where the NLOS parameters are estimated to improve the RBL performance. Without any prior information about the NLOS environment, the highly non-linear and non-convex RBL problem is transformed into a difference of convex (DC) programming, which can be solved by using the concave–convex procedure (CCCP) to determine the position of the rigid body sensors and the NLOS parameters. To avoid error accumulation, the obtained NLOS parameters are utilized to refine the localization performance of the rigid body sensors. Then, the accurate position and the orientation of the rigid body in two-Dimensional space are obtained according to the relative deflection angle method. To reduce the computational complexity, the singular value decomposition (SVD) method is employed to solve the problem in three-Dimensional space. Simulation results show that the proposed method can effectively improve the performance of the rigid body localization based on the wireless sensor network in NLOS environment.
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spelling doaj.art-1261ee497f19484f9cc013a14cf122982023-11-23T18:49:38ZengMDPI AGSensors1424-82202022-09-012218681010.3390/s22186810Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter EstimationPengwu Wan0Jian Wei1Jin Wang2Qiongdan Huang3School of Communications and Information Engineering & School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaSchool of Communications and Information Engineering & School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaSchool of Communications and Information Engineering & School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaSchool of Communications and Information Engineering & School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaIn wireless sensor network (WSN)-based rigid body localization (RBL) systems, the non-line-of-sight (NLOS) propagation of the wireless signals leads to severe performance deterioration. This paper focuses on the RBL problem under the NLOS environment based on the time of arrival (TOA) measurement between the sensors fixed on the rigid body and the anchors, where the NLOS parameters are estimated to improve the RBL performance. Without any prior information about the NLOS environment, the highly non-linear and non-convex RBL problem is transformed into a difference of convex (DC) programming, which can be solved by using the concave–convex procedure (CCCP) to determine the position of the rigid body sensors and the NLOS parameters. To avoid error accumulation, the obtained NLOS parameters are utilized to refine the localization performance of the rigid body sensors. Then, the accurate position and the orientation of the rigid body in two-Dimensional space are obtained according to the relative deflection angle method. To reduce the computational complexity, the singular value decomposition (SVD) method is employed to solve the problem in three-Dimensional space. Simulation results show that the proposed method can effectively improve the performance of the rigid body localization based on the wireless sensor network in NLOS environment.https://www.mdpi.com/1424-8220/22/18/6810non-line-of-sightrigid body localizationtime of arrivalconcave–convex procedure
spellingShingle Pengwu Wan
Jian Wei
Jin Wang
Qiongdan Huang
Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter Estimation
Sensors
non-line-of-sight
rigid body localization
time of arrival
concave–convex procedure
title Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter Estimation
title_full Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter Estimation
title_fullStr Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter Estimation
title_full_unstemmed Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter Estimation
title_short Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter Estimation
title_sort wireless sensor network based rigid body localization for nlos parameter estimation
topic non-line-of-sight
rigid body localization
time of arrival
concave–convex procedure
url https://www.mdpi.com/1424-8220/22/18/6810
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AT jianwei wirelesssensornetworkbasedrigidbodylocalizationfornlosparameterestimation
AT jinwang wirelesssensornetworkbasedrigidbodylocalizationfornlosparameterestimation
AT qiongdanhuang wirelesssensornetworkbasedrigidbodylocalizationfornlosparameterestimation