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Marine Geodesy Volume 38, 2015 - Issue 3
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Original Articles

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
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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]
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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
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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
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Jihong ShangSecond Institute of Oceanography, State Oceanic Administration, Hangzhou, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China
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Shoujun LiSecond Institute of Oceanography, State Oceanic Administration, Hangzhou, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China
Pages 225-240 | Received 17 Jul 2014, Accepted 05 Jan 2015, Published online: 21 Sep 2015
 
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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.

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