3-D Localization of Heterogeneous Underwater Networks Using Hybrid TOA-AOA Measurements Under Random DoS Attack

This article considers 3-D underwater environments cluttered with obstacles. This article handles how to localize all transceiver nodes in sensor networks. Each node can measure its depth, while measuring time of arrival (TOA), and angle of arrival (AOA) of signals generated from its nearby node. Each node is heterogeneous, such that the sensing noise of a node may be distinct from those of other nodes. In the 3-D sensor network, only one reference node is localized utilizing global navigation satellite system (GNSS). Considering obstacle-rich 3-D environments, our problem is to localize all heterogeneous transceiver nodes in the network, such that the position of only a single reference node is known a priori. In this article, we consider a large scale obstacle-rich environment, such that there exists a transceiver which cannot measure a direct signal of the reference node due to a limited sensing range. Since only one reference node is localized, one localizes every transceiver node in a breadth-first manner, starting from the reference node. This article further shows that the proposed localization scheme is robust to random DoS attack whose consecutive duration time is bounded above. To the best of our knowledge, this article is novel in hybrid TOA-AOA localization of the entire heterogeneous 3-D networks, considering the case where only one reference node exists in 3-D obstacle-rich environments. The effectiveness of the proposed 3-D localization scheme is verified utilizing MATLAB simulations.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-03-11
DOI
https://doi.org/10.1109/jiot.2025.3550398
Citations
4
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
4.58
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article

3-D Localization of Heterogeneous Underwater Networks Using Hybrid TOA-AOA Measurements Under Random DoS Attack

Jonghoek Kim
4 citations
IEEE Internet of Things Journal
Underwater Vehicles and Communication Systems
4.58
article

3-D Localization of Heterogeneous Underwater Networks Using Hybrid TOA-AOA Measurements Under Random DoS Attack

Jonghoek Kim
article en
4 citations

Abstract

This article considers 3-D underwater environments cluttered with obstacles. This article handles how to localize all transceiver nodes in sensor networks. Each node can measure its depth, while measuring time of arrival (TOA), and angle of arrival (AOA) of signals generated from its nearby node. Each node is heterogeneous, such that the sensing noise of a node may be distinct from those of other nodes. In the 3-D sensor network, only one reference node is localized utilizing global navigation satellite system (GNSS). Considering obstacle-rich 3-D environments, our problem is to localize all heterogeneous transceiver nodes in the network, such that the position of only a single reference node is known a priori. In this article, we consider a large scale obstacle-rich environment, such that there exists a transceiver which cannot measure a direct signal of the reference node due to a limited sensing range. Since only one reference node is localized, one localizes every transceiver node in a breadth-first manner, starting from the reference node. This article further shows that the proposed localization scheme is robust to random DoS attack whose consecutive duration time is bounded above. To the best of our knowledge, this article is novel in hybrid TOA-AOA localization of the entire heterogeneous 3-D networks, considering the case where only one reference node exists in 3-D obstacle-rich environments. The effectiveness of the proposed 3-D localization scheme is verified utilizing MATLAB simulations.

IEEE Internet of Things JournalVol. 12(12)
Sejong University (KR)
Life below water
Openalex Percentile: Top 6%
Underwater Vehicles and Communication Systems
4.58
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3-D Localization of Heterogeneous Underwater Networks Using Hybrid TOA-AOA Measurements Under Random DoS Attack — Jonghoek Kim · IEEE Internet of Things Journal (2025) | TGRS Research Map | TGRS