Low-rank approximation for underwater drone localization

Goo Jung Park, Jung Hoon Noh, Seong Jun Oh

Research output: Contribution to journalArticlepeer-review


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 languageEnglish
JournalICT Express
Publication statusAccepted/In press - 2023

Bibliographical 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:
© 2023 The Author(s)


  • Localization
  • SVD
  • Underwater

ASJC Scopus subject areas

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


Dive into the research topics of 'Low-rank approximation for underwater drone localization'. Together they form a unique fingerprint.

Cite this