A New Method of Automatic SVP Optimization Based on MOV Algorithm

Dineng ZhaoDepartment of Earth Sciences, Zhejiang University, Hangzhou, China;Second Institute of Oceanography, State Oceanic Administration, Hangzhou, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China

Ziyin WuDepartment of Earth Sciences, Zhejiang University, Hangzhou, China;Second Institute of Oceanography, State Oceanic Administration, Hangzhou, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, ChinaCorrespondence[email protected]

Jieqiong ZhouDepartment of Earth Sciences, Zhejiang University, Hangzhou, China;Second Institute of Oceanography, State Oceanic Administration, Hangzhou, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China

Jiabiao LiDepartment of Earth Sciences, Zhejiang University, Hangzhou, China;Second Institute of Oceanography, State Oceanic Administration, Hangzhou, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China

Jihong ShangSecond Institute of Oceanography, State Oceanic Administration, Hangzhou, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China

Shoujun LiSecond Institute of Oceanography, State Oceanic Administration, Hangzhou, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China

Abstract

We applied the maximum offset of sound velocity algorithm to sound velocity profile streamlining and optimization to overcome multibeam survey and data-processing efficiency problems. The impact of sound velocity profile streamlining on sounding data accuracy is evaluated. By automatically optimizing the threshold, the reduction rate of sound velocity profile data can reach over 90% and the standard deviation percentage error of sounding data can be controlled to within 0.1%. The optimized sound velocity profile data improved the operational efficiency of the multi-beam survey and data postprocessing by 3.4 times, indicating that this algorithm has practical value for engineering applications.

Keywords:

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

A New Method of Automatic SVP Optimization Based on MOV Algorithm

Information for

Open access

Opportunities

Help and information

A New Method of Automatic SVP Optimization Based on MOV Algorithm

Abstract

Reprints and Corporate Permissions

Academic Permissions

Related research

To cite this article:

Download citation

Information for

Open access

Opportunities

Help and information

Keep up to date

Your download is now in progress and you may close this window

Login or register to access this feature