Paper Info
Title
AUV-Aided Localization for Underwater Acoustic Sensor Networks With Current Field Estimation
Abstract
Accurate sensor localization is a crucial requirement for the deployment of underwater acoustic sensor networks (UASNs) in a large variety of applications. However, the asynchronous clock, stratification effect and mobility characteristics of underwater environment make it challenging to realize accurate node localization for UASNs. This paper develops an autonomous underwater vehicle (AUV) aided localization solution for UASNs, subjected to asynchronous clock, stratification effect and mobility constraints in cyber channels. A hybrid architecture including surface buoys, AUVs, active and passive sensor nodes, is first presented to construct a cooperative location-aware network. Then, an iterative least squares estimator is developed for AUVs to capture the unknown water current parameters, through which the relationship between propagation delay and location estimation can be established. With the assistance of AUVs, two asynchronous localization algorithms are designed to estimate the locations of active and passive sensor nodes. Particularly, motion and ray compensation strategies are jointly employed to improve the localization accuracy. It is worth noticing that, the proposed localization algorithms incorporate the current field estimation into the localization process of UASNs, and more importantly, they can eliminate the influences of asynchronous clock, stratification effect and node mobility together. Moreover, performance analyses for the proposed localization solution are also presented. Finally, simulation and experimental results reveal that the node localization accuracy in this paper can be significantly improved as compared with the other works.
Year
DOI
Venue
2020
10.1109/TVT.2020.2996513
IEEE Transactions on Vehicular Technology
Keywords
DocType
Volume
Localization,autonomous underwater vehicle (AUV),underwater acoustic sensor networks,current,mobility
Journal
69
Issue
ISSN
Citations 
8
0018-9545
1
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Jing Yan115120.02
Dongbo Guo210.34
Xiao-Yuan Luo327133.54
Xinping Guan42791253.38