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A New Method of Automatic SVP Optimization Based on MOV Algorithm |
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| Authors: | Dineng Zhao Jieqiong Zhou Jiabiao Li Jihong Shang Shoujun Li |
| Affiliation: | 1. Department of Earth Sciences, Zhejiang University, Hangzhou, China;2. Second Institute of Oceanography, State Oceanic Administration, Hangzhou, China;3. Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China;4. Second Institute of Oceanography, 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: | MOV algorithm SVP automatic optimization percentage error analysis multibeam echo sounding |