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Underwater optical sensor networks localization with limited connectivity

Underwater optical sensor networks localization with limited connectivity
Underwater optical sensor networks localization with limited connectivity

In this paper, a received signal strength (RSS) based localization technique is investigated for underwater optical wireless sensor networks (UOWSNs) where optical noise sources (e.g., sunlight, background, thermal, and dark current) and channel impairments of seawater (e.g., absorption, scattering, and turbulence) pose significant challenges. Hence, we propose a localization technique that works on the noisy ranging measurements embedded in a higher dimensional space and localize the sensor network in a low dimensional space. Once the neighborhood information is measured, a weighted network graph is constructed, which contains the one-hop neighbor distance estimations. A novel approach is developed to complete the missing distances in the kernel matrix. The output of the proposed technique is fused with Helmert transformation to refine the final location estimation with the help of anchors. The simulation results show that the root means square positioning error (RMSPE) of the proposed technique is more robust and accurate compared to baseline and manifold regularization.

Localization, Optical Communication, Sensor Networks, Underwater
1520-6149
3804-3808
IEEE
Saeed, Nasir
1a8fe222-ce62-48df-b04a-96ed8760e0a1
Celik, Abdulkadir
f8e72266-763c-4849-b38e-2ea2f50a69d0
Al-Naffouri, Tareq Y.
e4ec48c1-9987-49cd-b3ef-4942a3a3483e
Alouini, Mohamed Slim
3ccd5915-318e-4f4b-b47a-48257ab4c0eb
Saeed, Nasir
1a8fe222-ce62-48df-b04a-96ed8760e0a1
Celik, Abdulkadir
f8e72266-763c-4849-b38e-2ea2f50a69d0
Al-Naffouri, Tareq Y.
e4ec48c1-9987-49cd-b3ef-4942a3a3483e
Alouini, Mohamed Slim
3ccd5915-318e-4f4b-b47a-48257ab4c0eb

Saeed, Nasir, Celik, Abdulkadir, Al-Naffouri, Tareq Y. and Alouini, Mohamed Slim (2018) Underwater optical sensor networks localization with limited connectivity. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. vol. 2018-April, IEEE. pp. 3804-3808 . (doi:10.1109/ICASSP.2018.8461567).

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper, a received signal strength (RSS) based localization technique is investigated for underwater optical wireless sensor networks (UOWSNs) where optical noise sources (e.g., sunlight, background, thermal, and dark current) and channel impairments of seawater (e.g., absorption, scattering, and turbulence) pose significant challenges. Hence, we propose a localization technique that works on the noisy ranging measurements embedded in a higher dimensional space and localize the sensor network in a low dimensional space. Once the neighborhood information is measured, a weighted network graph is constructed, which contains the one-hop neighbor distance estimations. A novel approach is developed to complete the missing distances in the kernel matrix. The output of the proposed technique is fused with Helmert transformation to refine the final location estimation with the help of anchors. The simulation results show that the root means square positioning error (RMSPE) of the proposed technique is more robust and accurate compared to baseline and manifold regularization.

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More information

Published date: 10 September 2018
Additional Information: Publisher Copyright: © 2018 IEEE.
Venue - Dates: 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018, , Calgary, Canada, 2018-04-15 - 2018-04-20
Keywords: Localization, Optical Communication, Sensor Networks, Underwater

Identifiers

Local EPrints ID: 504469
URI: http://eprints.soton.ac.uk/id/eprint/504469
ISSN: 1520-6149
PURE UUID: bb0f9c5b-e358-4c4c-8428-25a5d4758ebf
ORCID for Abdulkadir Celik: ORCID iD orcid.org/0000-0001-9007-9979

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Date deposited: 09 Sep 2025 20:04
Last modified: 10 Sep 2025 13:50

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Contributors

Author: Nasir Saeed
Author: Abdulkadir Celik ORCID iD
Author: Tareq Y. Al-Naffouri
Author: Mohamed Slim Alouini

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