SSP Inversion for Weakening Refraction Errors in Deep-Sea Multibeam Bathymetry Using MOEA/D Algorithm

Refraction errors induced by inaccurate or insufficient sound-speed profiles (SSPs) can result in significant distortion of seafloor topography during multibeam bathymetric data processing. The current refraction error correction methods are focused on SSP inversion in shallow and medium water depth...

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Bibliographic Details
Published in:IEEE journal of oceanic engineering Vol. 50; no. 4; pp. 3117 - 3130
Main Authors: Li, Qianqian, Tong, Qian, Bu, Xianhai, Luo, Yu, Peng, Dongdong
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Accuracy
Acoustic beams
Acoustic measurements
Algorithms
Bathymetric data
Bathymetry
Covariance matrices
Data analysis
Data processing
Decomposition
Deep sea
Deep sea environments
Deep water
Distortion
Eigenvalues and eigenfunctions
Eigenvectors
Error correction
Evolutionary algorithms
Geologic measurements
Matrix decomposition
multibeam echosounder system (MBES)
multiobjective evolutionary algorithm based on decomposition (MOEA/D)
Ocean floor
Orthogonal functions
Pareto optimization
Ray tracing
Refraction
refraction errors
Sea measurements
sound-speed profile (SSP) inversion
Surveys
Swaths
Terrain
Water depth
ISSN:0364-9059, 1558-1691
Online Access:Get full text
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Summary:Refraction errors induced by inaccurate or insufficient sound-speed profiles (SSPs) can result in significant distortion of seafloor topography during multibeam bathymetric data processing. The current refraction error correction methods are focused on SSP inversion in shallow and medium water depth areas with relatively flat terrain. To address the problems encountered in deep-sea environments, an improved SSP inversion method is introduced that uses an empirical orthogonal function (EOF) decomposition and multiobjective evolutionary algorithm based on decomposition (MOEA/D). Initially, SSPs obtained from the Argo historical data set are decomposed by EOF decomposition, which extracts the orthogonal eigenvectors and the range of reconstruction coefficients. Then, the absolute mean value and standard deviation of depth differences within overlapping swathes are used as constraint conditions, forming dual objective functions. The MOEA/D algorithm is employed to determine the optimal EOF coefficients. Finally, ray tracing is conducted using the inverted SSP to correct the seafloor distortion. The method was verified using experimental data in complex deep-sea terrain. The maximum depth difference within the overlapping area of adjacent swaths notably decreases from 14.9 to 5.6 m, and the root mean square error decreases from 6.4 to 1.2 m.
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ISSN:0364-9059
1558-1691
DOI:10.1109/JOE.2025.3566902