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JMSE
Special Issues
Techniques and Challenges in Underwater Localization
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Techniques and Challenges in Underwater Localization

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (15 July 2019) | Viewed by 2262

Special Issue Editor

Dr.-Ing. Marc Hildebrandt

E-Mail Website
Guest Editor
German Research Institute for Artificial Intelligence Robotics Innovation Center Bremen (DFKI-RIC), Bremen, Germany
Interests: artificial intelligence; underwater robotics; mobile vehicle localization; vehicle design; image processing

Special Issue Information

Dear Colleagues,

Localization has always been a very important challenge in the application of underwater robotic vehicles. As the number of applications and their complexity have grown, it has become an important research topic. This Special Issue aims to create a comprehensive overview of the challenges, methods and open research questions in this field. Both new approaches, as well as proven and tested techniques, are invited. In order to ensure a high quality of the contributions, it is strongly advised to submit work which has been validated in some way, e.g., experimentally or with simulation environments suitable for the complex application scenario.

I am very much looking forwards to receiving interesting work, please feel free to contact me before considering a contribution if you are unsure if it fits the requirements for this Special Issue.

With kind regards,

Dr. -Ing. Marc Hildebrandt
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • AUV
  • ROV
  • Navigation
  • SLAM
  • Localization
  • Dead-Reckoning
  • Underwater Vehicles

Published Papers (1 paper)

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Research

14 pages, 3728 KiB  
Article
Joint Inversion for Sound Speed Field and Moving Source Localization in Shallow Water
by Miao Dai, Yaan Li and Kunde Yang
J. Mar. Sci. Eng. 2019, 7(9), 295; https://doi.org/10.3390/jmse7090295 - 29 Aug 2019
Cited by 4 | Viewed by 2009
Abstract
This paper develops a joint approach for time-evolving sound speed field (SSF) inversion and moving source localization in shallow water environment. The SSF is parameterized in terms of the first three empirical orthogonal function (EOF) coefficients. The approach treats both first three EOF [...] Read more.
This paper develops a joint approach for time-evolving sound speed field (SSF) inversion and moving source localization in shallow water environment. The SSF is parameterized in terms of the first three empirical orthogonal function (EOF) coefficients. The approach treats both first three EOF coefficients and source parameters (e.g., source depth, range and speed) as state vectors of evolving with time, and a measurement vector that incorporates acoustic information via a vertical line array (VLA), and then the inversion problem is formulated in a state-space model. The processors of the extended Kalman filter (EKF) and ensemble Kalman filter (EnKF) are used to estimate the evolution of those six parameters. Simulation results verify the proposed approach, which enable it to invert the SSF and locate the moving source simultaneously. The root-mean-square-error (RMSE) is employed to evaluate the effectiveness of this proposed approach. The interfile comparison shows that the EnKF outperform the EKF. For the EnKF, the robustness of the approach under the sparse vertical array configuration is verified. Moreover, the impact of the source-VLA deployment on the estimation is also concerned. Full article
(This article belongs to the Special Issue Techniques and Challenges in Underwater Localization)
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