Coastal SLAM With Marine Radar for USV Operation in GPS-Restricted Situations

Cited 39 time in webofscience Cited 21 time in scopus
  • Hit : 478
  • Download : 0
The global positioning system (GPS) has become an indispensable navigation sensor for field operations with unmanned surface vehicles (USVs) in marine environments. However, GPS may not always be available, even in open outdoor areas, because it is vulnerable to natural interference and malicious jamming attacks. Thus, an alternative navigation system is required when the use of GPS is restricted or prohibited. In such circumstances, a marine radar, which is a standard sensor in amarine vehicle including USV, can be used for localization in coastal areas. The marine radar can extract landmark features of the surrounding coastlines. These features can be utilized for relative navigation with respect to the detected coastlines. However, coastline maps based on radar signatures may be unavailable in unexplored areas, and they may be unreliable in coastal areas with high tidal elevations. In this study, the relative navigation with respect to the surrounding coastlines is performed in the framework of simultaneous localization and mapping (SLAM) for a USV operation in coastal waters. In particular, coastline features are parameterized by using B-splines for efficient map management, instead of the conventional point cloud representation. To verify and demonstrate the performance of the proposed coastal SLAM algorithm, field experiments were conducted in actual coastal environments. The results are presented and discussed in this paper.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2019-04
Language
English
Article Type
Article; Proceedings Paper
Citation

IEEE JOURNAL OF OCEANIC ENGINEERING, v.44, no.2, pp.300 - 309

ISSN
0364-9059
DOI
10.1109/JOE.2018.2883887
URI
http://hdl.handle.net/10203/261825
Appears in Collection
ME-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 39 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0