Parameter optimization and configuration of the CUBE algorithm for shallow water survey

Yong Zhou

doi:10.1117/12.2665552

31 January 2023 Parameter optimization and configuration of the CUBE algorithm for shallow water survey

Yong Zhou

Proceedings Volume 12505, Earth and Space: From Infrared to Terahertz (ESIT 2022); 1250521 (2023) https://doi.org/10.1117/12.2665552
Event: Earth and Space: From Infrared to Terahertz (ESIT 2022), 2022, Nantong, China

Abstract

The processing of bathymetric data of multi-beam echo sounders is required in the hydrographic and oceanographic field. The algorithm CUBE allows automatic processing of data to estimate the depth of the sea floor through multi-beam data. To implement the CUBE algorithm, it is important to set the parameters in the data processing. Depending on the complexity of the survey, the optimization CUBE setting is essential to ensure the quality of results of data processing. In this paper, the optimization of CUBE algorithm, which is based on the configuration of the algorithm parameterization, is used to optimize the parameters of CUBE algorithm to improve the quality of data processing on shallow water for multi-beam echo-sounder. First, the behavior of CUBE is described through some different parameters to a new parameterization more suited to the EM2040C sounders. Then, tests of the CUBE parameterization are carried out with the aim of obtaining an optimal parameter configuration. Finally, the influence of parameters is analyzed by statistics methods to explain the feasibility of using CUBE algorithm to parameterize data processing on shallow water. Experimental results with the shallow water dataset demonstrate the majorization and effectiveness of the CUBE parameters setting for situations of the survey in areas of small depths.

Citation Download Citation

Yong Zhou "Parameter optimization and configuration of the CUBE algorithm for shallow water survey", Proc. SPIE 12505, Earth and Space: From Infrared to Terahertz (ESIT 2022), 1250521 (31 January 2023); https://doi.org/10.1117/12.2665552

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KEYWORDS

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Statistical analysis

Data processing

Optimization (mathematics)

Data modeling

Velocity measurements

Error analysis

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