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Remote Sensing
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Navigation, Localization and Applications for Unmanned Marine Vehicles and Systems
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Navigation, Localization and Applications for Unmanned Marine Vehicles and Systems

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 9649

Special Issue Editor

Dr. Nak Yong Ko

E-Mail Website
Guest Editor
Department of Electronic Engineering, Chosun University, Gwangju, Republic of Korea
Interests: mobile robots; marine vehicles; autonomous vehicles; navigation; estimation

Special Issue Information

Dear Colleagues,

The development of autonomous or partially autonomous underwater vehicles and systems has made many tasks that previously depended on manned vehicles or remote and indirect manual operations possible. As an important tool of ocean exploration, unmanned underwater surface vehicles and systems can be used for scientific research, such as underwater terrain recognition, seafloor mapping, and marine ecological monitoring. In addition, they also play an important role in marine resource exploration and development, underwater rescue, and military reconnaissance. Compared with fixed marine sensors, unmanned vehicles and systems with some autonomy can conduct oceanographic surveys with higher resolution and quality, which is an important development trend in marine exploration. However, in the underwater environment, the communication, positioning, tracking and navigation of underwater systems are still very challenging due to the difficulty of wireless communication and the use of the global navigation satellite system. In order to solve such problems, research on acoustic base line systems, estimation techniques and other tools to assist underwater positioning and navigation emerge in an endless stream, and also provide new ideas for reliable trajectory/path tracking and obstacle avoidance algorithms in unmanned marine vehicles.

It is our pleasure to announce the launch of a new Special Issue in Remote Sensing, whose goal is to collect research results on the application of unmanned marine vehicles and systems in marine mission monitoring, navigation and positioning, and its latest development prospects. Research topics include, but are not limited to, surface/underwater vehicles, navigation and control, underwater acoustic communication, motion planning for tracking and the path and trajectory, new advances in the cooperative navigation of multiple vehicles and systems, and the use of machine learning and intelligence in navigation and positioning.

Dr. Nak Yong Ko
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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

  • unmanned surface/underwater vehicles
  • navigation/localization
  • acoustic communication
  • motion planning
  • cooperative navigation of multiple vehicles and systems
  • guidance, tracking, and control
  • ocean monitoring
  • sensor fusion for navigation and positioning
  • machine learning and AI for marine navigation

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

25 pages, 5796 KiB  
Article
Measuring Tilt with an IMU Using the Taylor Algorithm
by Jerzy Demkowicz
Remote Sens. 2024, 16(15), 2800; https://doi.org/10.3390/rs16152800 - 30 Jul 2024
Viewed by 3119
Abstract
This article addresses the important problem of tilt measurement and stabilization. This is particularly important in the case of drone stabilization and navigation in underwater environments, multibeam sonar mapping, aerial photogrammetry in densely urbanized areas, etc. The tilt measurement process involves the fusion [...] Read more.
This article addresses the important problem of tilt measurement and stabilization. This is particularly important in the case of drone stabilization and navigation in underwater environments, multibeam sonar mapping, aerial photogrammetry in densely urbanized areas, etc. The tilt measurement process involves the fusion of information from at least two different sensors. Inertial sensors (IMUs) are unique in this context because they are both autonomous and passive at the same time and are therefore very attractive. Their calibration and systematic errors or bias are known problems, briefly discussed in the article due to their importance, and are relatively simple to solve. However, problems related to the accumulation of these errors over time and their autonomous and dynamic correction remain. This article proposes a solution to the problem of IMU tilt calibration, i.e., the pitch and roll and the accelerometer bias correction in dynamic conditions, and presents the process of calculating these parameters based on combined accelerometer and gyroscope records using a new approach based on measuring increments or differences in tilt measurement. Verification was performed by simulation under typical conditions and for many different inertial units, i.e., IMU devices, which brings the proposed method closer to the real application context. The article also addresses, to some extent, the issue of navigation, especially in the context of dead reckoning. Full article
(This article belongs to the Special Issue Navigation, Localization and Applications for Unmanned Marine Vehicles and Systems)
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19 pages, 5350 KiB  
Article
An Adaptive Tracking Method for Moving Target in Fluctuating Reverberation Environment
by Ning Wang, Rui Duan, Kunde Yang, Zipeng Li and Zhanchao Liu
Remote Sens. 2024, 16(9), 1569; https://doi.org/10.3390/rs16091569 - 28 Apr 2024
Cited by 1 | Viewed by 1134
Abstract
In environments with a low signal-to-reverberation ratio (SRR) characterized by fluctuations in clutter number and distribution, particle filter-based tracking methods may experience significant fluctuations in the posterior probability of existence. This can lead to interruptions or even loss of the target trajectory. To [...] Read more.
In environments with a low signal-to-reverberation ratio (SRR) characterized by fluctuations in clutter number and distribution, particle filter-based tracking methods may experience significant fluctuations in the posterior probability of existence. This can lead to interruptions or even loss of the target trajectory. To address this issue, an adaptive PF-based tracking method (APF) with joint reverberation suppression is proposed. This method establishes the state space model under the Bayesian framework and implements it through particle filtering. To keep the weak target echoes, all the non-zero entries contained in the sparse matrix processed by the low-rank and sparsity decomposition (LRSD) are treated as the measurements. The prominent feature of this approach is introducing an adaptive measurement likelihood ratio (AMLR) into the posterior update step, which solves the problem of unstable tracking due to the strong fluctuation in the number of point measurements per frame. The proposed method is verified by four shallow water experimental datasets obtained by an active sonar with a uniform horizontal linear array. The results demonstrate that the tracking frame success ratio of the proposed method improved by over 14% compared with the conventional PF tracking method. Full article
(This article belongs to the Special Issue Navigation, Localization and Applications for Unmanned Marine Vehicles and Systems)
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18 pages, 8184 KiB  
Article
Two-Step Correction Based on In-Situ Sound Speed Measurements for USBL Precise Real-Time Positioning
by Shuang Zhao, Huimin Liu, Shuqiang Xue, Zhenjie Wang and Zhen Xiao
Remote Sens. 2023, 15(20), 5046; https://doi.org/10.3390/rs15205046 - 20 Oct 2023
Cited by 3 | Viewed by 2134
Abstract
The ultra-short baseline (USBL) positioning system has been widely used for autonomous and remotely operated vehicle (ARV) positioning in marine resource surveying and ocean engineering fields due to its flexible installation and portable operation. Errors related to the sound speed are a critical [...] Read more.
The ultra-short baseline (USBL) positioning system has been widely used for autonomous and remotely operated vehicle (ARV) positioning in marine resource surveying and ocean engineering fields due to its flexible installation and portable operation. Errors related to the sound speed are a critical factor limiting the positioning performance. The conventional strategy adopts a fixed sound velocity profile (SVP) to correct the spatial variation, especially in the vertical direction. However, SVP is actually time-varying, and ignoring this kind of variation will lead to a worse estimation of ARVs’coordinates. In this contribution, we propose a two-step sound speed correction method, where, firstly, the deviation due to the acoustic ray bending effect is corrected by the depth-based ray-tracing policy with the fixed SVP. Then, the temporal variation of SVP is considered, and the fixed SVP is adaptively adjusted according to the in situ sound velocity (SV) measurements provided by the conductivity–temperature–depth (CTD) sensor equipped at the ARV. The proposed method is verified by semi-physical simulation and sea-trail dataset in the South China Sea. When compared to the fixed-SVP method, average positioning accuracy with the resilient SVP be improved by 8%, 21%, and 26% in the east, north, and up directions, respectively. The results demonstrate that the proposed method can efficiently improve the adaptability of sound speed observations and deliver better performance in USBL real-time positioning. Full article
(This article belongs to the Special Issue Navigation, Localization and Applications for Unmanned Marine Vehicles and Systems)
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Graphical abstract

12 pages, 4170 KiB  
Communication
Demonstration of the Feasibility of the Korean eLoran System as a Resilient PNT in a Testbed
by Pyo-Woong Son, Sul Gee Park, Younghoon Han, Kiyeol Seo and Tae Hyun Fang
Remote Sens. 2023, 15(14), 3586; https://doi.org/10.3390/rs15143586 - 18 Jul 2023
Cited by 11 | Viewed by 2120
Abstract
With the increasing utilization of location information, attempts to improve the safety of absolute positioning coordinates, which have depended on global navigation satellite systems (GNSSs), such as the Global Positioning System (GPS), are underway. Among these, enhanced long range navigation (eLoran) is the [...] Read more.
With the increasing utilization of location information, attempts to improve the safety of absolute positioning coordinates, which have depended on global navigation satellite systems (GNSSs), such as the Global Positioning System (GPS), are underway. Among these, enhanced long range navigation (eLoran) is the most technically developed system. In Korea, related technologies have been developed since 2016, and a testbed for eLoran performance evaluation, which is currently in operation as a pilot service, was completed in 2021. We analyze the position accuracy of the eLoran pilot service to use it as an alternative when GNSS usage is challenging within Korea’s eLoran testbed. We evaluated the accuracy of the absolute position using the eLoran system by sailing up to 160 km away from the Incheon testbed transmitter according to four navigation stages (inland waterway, port approach, coastal, and ocean) classified by the International Maritime Organization (IMO). To validate the eLoran positioning performance in which an additional secondary factor (ASF) map is not provided, we propose a differential GPS (DGPS) position-based ASF estimation technique. Based on this study, Korea’s eLoran system can calculate the absolute position with an accuracy of approximately 15 m with 95% probability at the port-approach stage. Full article
(This article belongs to the Special Issue Navigation, Localization and Applications for Unmanned Marine Vehicles and Systems)
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