Navigation of Unmanned Surface Vehicles Using Underwater Geophysical Sensing
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jung, Jongdae | - |
dc.contributor.author | Park, Jeonghong | - |
dc.contributor.author | Choi, Jinwoo | - |
dc.contributor.author | Choi, Hyun-Taek | - |
dc.date.accessioned | 2021-08-03T04:23:03Z | - |
dc.date.available | 2021-08-03T04:23:03Z | - |
dc.date.issued | 2020-11 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/317 | - |
dc.description.abstract | Underwater geophysical properties can provide useful information for surface navigation, particularly in situations where a global navigation satellite system is unavailable. Unmanned surface vehicles (USVs) equipped with geophysical sensors can measure certain types of underwater properties related to Earth geophysics. For example, multibeam echosounders can obtain an array of sonar ranges for underwater terrains, and magnetometers can measure geomagnetic vector fields. These measurements can be used to track vehicle poses if pre-surveyed geophysical maps are provided. This paper proposes geophysical navigation of USVs using a multibeam sonar and magnetometer. The navigation algorithm is implemented within a particle filter framework, and we designed observation models for each geophysical sensor. To avoid the particle impoverishment problem of the conventional terrain based navigation, a terrain roughness measure is employed to modify the weight update and resampling steps of the standard particle filter framework. We conducted field experiments in an inland water environment using the designed surface vehicle, and validated enhanced tracking performance of the proposed methods by comparing the methods with conventional approaches. | - |
dc.format.extent | 11 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Navigation of Unmanned Surface Vehicles Using Underwater Geophysical Sensing | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/ACCESS.2020.3038816 | - |
dc.identifier.scopusid | 2-s2.0-85097652170 | - |
dc.identifier.wosid | 000595985000001 | - |
dc.identifier.bibliographicCitation | IEEE ACCESS, v.8, pp 208707 - 208717 | - |
dc.citation.title | IEEE ACCESS | - |
dc.citation.volume | 8 | - |
dc.citation.startPage | 208707 | - |
dc.citation.endPage | 208717 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordAuthor | Magnetic field measurement | - |
dc.subject.keywordAuthor | Atmospheric measurements | - |
dc.subject.keywordAuthor | Sonar measurements | - |
dc.subject.keywordAuthor | Geophysical measurements | - |
dc.subject.keywordAuthor | Sonar navigation | - |
dc.subject.keywordAuthor | Particle measurements | - |
dc.subject.keywordAuthor | Particle filters | - |
dc.subject.keywordAuthor | Geophysical navigation | - |
dc.subject.keywordAuthor | magnetometer | - |
dc.subject.keywordAuthor | multibeam echosounder | - |
dc.subject.keywordAuthor | particle filter | - |
dc.subject.keywordAuthor | unmanned surface vehicle | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(34103) 대전광역시 유성구 유성대로1312번길 32042-866-3114
COPYRIGHT 2021 BY KOREA RESEARCH INSTITUTE OF SHIPS & OCEAN ENGINEERING. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.