Circular synthetic aperture sonar results from autonomous underwater vehicle trials

2008 ◽  
Vol 123 (5) ◽  
pp. 3899-3899 ◽  
Author(s):  
Roy E. Hansen ◽  
Torstein Olsmo Sæbo/ ◽  
Hayden J. Callow
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Synthetic Aperture ◽  
Synthetic Aperture Sonar

Autonomous Underwater Vehicle equipped with Interferometric Real and Synthetic Aperture Sonar

2016 ◽  
Author(s):  
Kenji Nagahashi ◽  
Akira Asada ◽  
Katsunori Mizuno ◽  
Mitsuhiro Kojima ◽  
Fuyuki Katase ◽  
...  
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Synthetic Aperture ◽  
Synthetic Aperture Sonar

scholarly journals The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE

2020 ◽  
Vol 12 (8) ◽  
pp. 1344 ◽  
Author(s):  
Karolina Zwolak ◽  
Rochelle Wigley ◽  
Aileen Bohan ◽  
Yulia Zarayskaya ◽  
Evgenia Bazhenova ◽  
...  
Keyword(s):  
Deep Water ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Unmanned Vehicles ◽  
Ionian Sea ◽  
Automatic Data ◽  
Multibeam Echosounder ◽  
Synthetic Aperture Sonar ◽  
Unmanned Surface Vessel ◽  
Surface Vessel

The methods of data collection, processing, and assessment of the quality of the results of a survey conducted at the Southern Ionian Sea off the Messinian Peninsula, Greece are presented. Data were collected by the GEBCO-Nippon Foundation Alumni Team, competing in the Shell Ocean Discovery XPRIZE, during the Final Round of the competition. Data acquisition was conducted by the means of unmanned vehicles only. The mapping system was composed of a single deep water AUV (Autonomous Underwater Vehicle), equipped with a high-resolution synthetic aperture sonar HISAS 1032 and multibeam echosounder EM 2040, partnered with a USV (Unmanned Surface Vessel). The USV provided positioning data as well as mapping the seafloor from the surface, using a hull-mounted multibeam echosounder EM 304. Bathymetry and imagery data were collected for 24 h and then processed for 48 h, with the extensive use of cloud technology and automatic data processing. Finally, all datasets were combined to generate a 5-m resolution bathymetric surface, as an example of the deep-water mapping capabilities of the unmanned vehicles’ cooperation and their sensors’ integration.

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