Low-rank approximation for underwater drone localization

Goo Jung Park; Jung Hoon Noh; Seong Jun Oh

doi:10.1016/j.icte.2023.03.010

Low-rank approximation for underwater drone localization

Goo Jung Park, Jung Hoon Noh, Seong Jun Oh

School of Cybersecurity

Research output: Contribution to journal › Article › peer-review

Abstract

We herein propose a low-approximated least-squares method for underwater drone localization that does not require depth information. On the basis of error analysis, we propose a rule to deploy a set of surface drones that minimizes the impact of measurement errors such as GPS or distance measurement errors. The Evaluation results indicate that the proposed method outperforms the least-squares method when depth information is not provided.

Original language	English
Journal	ICT Express
DOIs	https://doi.org/10.1016/j.icte.2023.03.010
Publication status	Accepted/In press - 2023

Keywords

Localization
SVD
Underwater

ASJC Scopus subject areas

Software
Information Systems
Hardware and Architecture
Computer Networks and Communications
Artificial Intelligence

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10.1016/j.icte.2023.03.010

Cite this

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title = "Low-rank approximation for underwater drone localization",

abstract = "We herein propose a low-approximated least-squares method for underwater drone localization that does not require depth information. On the basis of error analysis, we propose a rule to deploy a set of surface drones that minimizes the impact of measurement errors such as GPS or distance measurement errors. The Evaluation results indicate that the proposed method outperforms the least-squares method when depth information is not provided.",

keywords = "Localization, SVD, Underwater",

author = "Park, {Goo Jung} and Noh, {Jung Hoon} and Oh, {Seong Jun}",

note = "Funding Information: This work was supported by the Nuclear Safety Research Program through the Korea Foundation Of Nuclear Safety (KoFONS) using the financial resource granted by the Nuclear Safety and Security Commission (NSSC) of the Republic of Korea (No. 1805006). Publisher Copyright: {\textcopyright} 2023 The Author(s)",

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doi = "10.1016/j.icte.2023.03.010",

language = "English",

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T1 - Low-rank approximation for underwater drone localization

AU - Park, Goo Jung

AU - Noh, Jung Hoon

AU - Oh, Seong Jun

N1 - Funding Information: This work was supported by the Nuclear Safety Research Program through the Korea Foundation Of Nuclear Safety (KoFONS) using the financial resource granted by the Nuclear Safety and Security Commission (NSSC) of the Republic of Korea (No. 1805006). Publisher Copyright: © 2023 The Author(s)

PY - 2023

Y1 - 2023

N2 - We herein propose a low-approximated least-squares method for underwater drone localization that does not require depth information. On the basis of error analysis, we propose a rule to deploy a set of surface drones that minimizes the impact of measurement errors such as GPS or distance measurement errors. The Evaluation results indicate that the proposed method outperforms the least-squares method when depth information is not provided.

AB - We herein propose a low-approximated least-squares method for underwater drone localization that does not require depth information. On the basis of error analysis, we propose a rule to deploy a set of surface drones that minimizes the impact of measurement errors such as GPS or distance measurement errors. The Evaluation results indicate that the proposed method outperforms the least-squares method when depth information is not provided.

KW - Localization

KW - SVD

KW - Underwater

UR - http://www.scopus.com/inward/record.url?scp=85151701834&partnerID=8YFLogxK

U2 - 10.1016/j.icte.2023.03.010

DO - 10.1016/j.icte.2023.03.010

M3 - Article

AN - SCOPUS:85151701834

SN - 2405-9595

JO - ICT Express

JF - ICT Express

ER -

Low-rank approximation for underwater drone localization

Abstract

Keywords

ASJC Scopus subject areas

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