Robust silent localization of underwater acoustic sensor network using mobile anchor(s)

Underwater acoustic sensor networks (UWASNs) can revolutionize the subsea domain by enabling low-cost monitoring of subsea assets and the marine environment. Accurate localization of the UWASNs is essential for these applications. In general, range-based localization techniques are preferred for their high accuracy in estimated locations. However, they can be severely affected by variable sound speed, multipath spreading, and other effects of the acoustic channel. In addition, an inefficient localization scheme can consume a significant amount of energy, reducing the effective life of the battery-powered sensor nodes. In this paper, we propose robust, efficient, and practically implementable localization schemes for static UWASNs. The proposed schemes are based on the Time-Difference-of-Arrival (TDoA) measurements and the nodes are localized passively, i.e., by just listening to beacon signals from multiple anchors, thus saving both the channel bandwidth and energy. The robustness in location estimates is achieved by considering an appropriate statistical noise model based on a plausible acoustic channel model and certain practical assumptions. To overcome the practical challenges of deploying and maintaining multiple permanent anchors for TDoA measurements, we propose practical schemes of using a single or multiple surface vehicles as virtual anchors. The robustness of localization is evaluated by simulations under realistic settings. By combining a mobile anchor(s) scheme with a robust estimator, this paper presents a complete package of efficient, robust, and practically usable localization schemes for low-cost UWASNs.

Citation

Mourya, Rahul, Mauro Dragone, and Yvan Petillot. 2021. "Robust Silent Localization of Underwater Acoustic Sensor Network Using Mobile Anchor(s)" Sensors 21, no. 3: 727. https://doi.org/10.3390/s21030727

PubMed ID

33494511 (pubmed)

Additional Links

https://www.mdpi.com/1424-8220/21/3/727

Type

Journal article

Language

en

Description

© 2021 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/s21030727

ISSN

1424-8220

EISSN

1424-8220

Rights

Licence for published version: Creative Commons Attribution 4.0 International

cb

Collections

Faculty of Science and Engineering