A Novel Approach to Installation Bias Overall Calibration in Multibeam Echosounder Systems Based on Prior Submarine Topography
Recalibration of installation bias is critical in seafloor mapping with multibeam echosounder systems when transducers are reinstalled. However, present calibrating techniques are often difficult and inefficient. In the present work, a novel approach for overall calibration of installation bias based on prior submarine topography was proposed. Initially, bathymetric point data were merged to provide a point cloud dataset containing the measured topography, uncalibrated for installation bias, and the accurate prior topography. Then, a point cloud registration method was used to align the measured topography with the prior topography to obtain the matching point pairs. Finally, with these matched point pairs, the multibeam echosounder system installation bias was resolved by the total least squares adjustment approach. Experiments on complex and flat submarine terrain validated the accuracy and efficacy of our proposed method: the calibration method improved the internal and external consistency of bathymetric data, regardless of whether the terrain was flat or complex. The proposed method matched the Patch Test in computational accuracy while offering substantial advantages in terms of simplicity and operational efficiency, indicating its potential for practical engineering applications.
Authors
- Xiaohan Yu
- Wei Yuan (ORCID: https://orcid.org/0000-0002-3158-3486)
- Shaohua Jin (ORCID: https://orcid.org/0009-0006-3315-9335)
- Ding Liang (ORCID: https://orcid.org/0000-0002-9435-3901)
- Yang Cui (ORCID: https://orcid.org/0009-0007-3737-6502)
Institutions
- Dalian Ocean University (CN)
- Dalian Naval Academy
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3585434
- Primary Topic
- Underwater Acoustics Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China