Dynamic Reference Selection-Based Self-Localization Algorithm for Drifted Underwater Acoustic Networks

Self-localization has become one of the major areas of research in drifted underwater acoustic networks (DUANs) since many applications are based on the knowledge of nodes’ positions. However, self-localization for DUANs faces two main challenges: the insufficient anchors and the varying n...

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Main Authors: Jingjie Gao, Xiaohong Shen, Haodi Mei, Zhichen Zhang
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/18/3920
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author Jingjie Gao
Xiaohong Shen
Haodi Mei
Zhichen Zhang
author_facet Jingjie Gao
Xiaohong Shen
Haodi Mei
Zhichen Zhang
author_sort Jingjie Gao
collection DOAJ
description Self-localization has become one of the major areas of research in drifted underwater acoustic networks (DUANs) since many applications are based on the knowledge of nodes’ positions. However, self-localization for DUANs faces two main challenges: the insufficient anchors and the varying network topology. Both affect the localization performance seriously. In this paper, we focus on these two challenges and propose a dynamic reference selection-based self-localization algorithm for DUANs (DRSL) to improve the localization performance. First, an optimal reference selection scheme is presented to solve the insufficient anchors’ problem. The selected optimal reference node can not only assist the insufficient anchors in accomplishing the localization procedure, but also obviously increase the localization accuracy. Based on the proposed optimal reference selection scheme, a dynamic reference selection-based self-localization algorithm is proposed to solve the topology changing problem. The proposed algorithm can improve the localization performance for DUANs significantly by selecting the reference node dynamically according to the predicted network topology, which is more suitable for DUANs with mobile sensor nodes. Simulation results show that the proposed DRSL algorithm can increase the localization accuracy greatly with insufficient anchor nodes and varying network topology. In addition, DRSL algorithm also has a lower communication cost than other anchor-free approaches, which distinctly demonstrates the advantages of the proposed DRSL algorithm.
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spelling doaj.art-305968157e444c1591707649081f9c4f2022-12-22T02:55:47ZengMDPI AGSensors1424-82202019-09-011918392010.3390/s19183920s19183920Dynamic Reference Selection-Based Self-Localization Algorithm for Drifted Underwater Acoustic NetworksJingjie Gao0Xiaohong Shen1Haodi Mei2Zhichen Zhang3School of Information Engineering, Chang’an University, Xi’an 710064, ChinaKey Laboratory of Ocean Acoustics and Sensing, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaKey Laboratory of Ocean Acoustics and Sensing, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaKey Laboratory of Ocean Acoustics and Sensing, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSelf-localization has become one of the major areas of research in drifted underwater acoustic networks (DUANs) since many applications are based on the knowledge of nodes’ positions. However, self-localization for DUANs faces two main challenges: the insufficient anchors and the varying network topology. Both affect the localization performance seriously. In this paper, we focus on these two challenges and propose a dynamic reference selection-based self-localization algorithm for DUANs (DRSL) to improve the localization performance. First, an optimal reference selection scheme is presented to solve the insufficient anchors’ problem. The selected optimal reference node can not only assist the insufficient anchors in accomplishing the localization procedure, but also obviously increase the localization accuracy. Based on the proposed optimal reference selection scheme, a dynamic reference selection-based self-localization algorithm is proposed to solve the topology changing problem. The proposed algorithm can improve the localization performance for DUANs significantly by selecting the reference node dynamically according to the predicted network topology, which is more suitable for DUANs with mobile sensor nodes. Simulation results show that the proposed DRSL algorithm can increase the localization accuracy greatly with insufficient anchor nodes and varying network topology. In addition, DRSL algorithm also has a lower communication cost than other anchor-free approaches, which distinctly demonstrates the advantages of the proposed DRSL algorithm.https://www.mdpi.com/1424-8220/19/18/3920self-localizationdrifted underwater acoustic networksreference selection
spellingShingle Jingjie Gao
Xiaohong Shen
Haodi Mei
Zhichen Zhang
Dynamic Reference Selection-Based Self-Localization Algorithm for Drifted Underwater Acoustic Networks
Sensors
self-localization
drifted underwater acoustic networks
reference selection
title Dynamic Reference Selection-Based Self-Localization Algorithm for Drifted Underwater Acoustic Networks
title_full Dynamic Reference Selection-Based Self-Localization Algorithm for Drifted Underwater Acoustic Networks
title_fullStr Dynamic Reference Selection-Based Self-Localization Algorithm for Drifted Underwater Acoustic Networks
title_full_unstemmed Dynamic Reference Selection-Based Self-Localization Algorithm for Drifted Underwater Acoustic Networks
title_short Dynamic Reference Selection-Based Self-Localization Algorithm for Drifted Underwater Acoustic Networks
title_sort dynamic reference selection based self localization algorithm for drifted underwater acoustic networks
topic self-localization
drifted underwater acoustic networks
reference selection
url https://www.mdpi.com/1424-8220/19/18/3920
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AT xiaohongshen dynamicreferenceselectionbasedselflocalizationalgorithmfordriftedunderwateracousticnetworks
AT haodimei dynamicreferenceselectionbasedselflocalizationalgorithmfordriftedunderwateracousticnetworks
AT zhichenzhang dynamicreferenceselectionbasedselflocalizationalgorithmfordriftedunderwateracousticnetworks