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A Precise Method to Calibrate Dynamic Integration Errors in Shallow- and Deep-Water Multibeam Bathymetric Data.

Authors :
Bu, Xianhai
Mei, Sai
Yang, Fanlin
Luan, Zhendong
Xu, Fangzheng
Luo, Yu
Source :
IEEE Transactions on Geoscience & Remote Sensing. Jan2022, Vol. 60 Issue 1, p1-14. 14p.
Publication Year :
2022

Abstract

Acoustic remote sensing with multibeam echo-sounder systems (MBESs) has been extensively used for coastal and ocean survey works. The imperfect integration of multibeam echo sounder and motion sensor can introduce integration errors, which manifest as high-frequency wobbles in swaths and hinder the accurate expression of high-resolution seabed topographic maps. To address this issue, a precise method is developed to calibrate these integration errors based on a simplified georeferenced model. First, an equivalent attitude coordinate (EAC) system is defined to represent mutual transformation between equivalent attitudes and the beam launch vector; then, with the help of equivalent attitudes, a simplified footprint georeferenced model is deduced that considers the effect of the parameterized integration errors (including time delay, motion scale, yaw misalignment, and lever arm errors); finally, in a selected flat region, integration errors are inverted by regressing the bathymetric data to the corresponding fitted plane via the differential evolution (DE) algorithm. The results indicate that the proposed method can effectively eliminate wobbles in multibeam bathymetries caused by single or multiple integration errors in both shallow- and deep-water areas. By comparing the data before and after calibration with the in situ measurements, the accuracy of the calibrated shallow- and deep-water data is controlled within approximately 0.15% and 0.06% of the water depth, respectively. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01962892
Volume :
60
Issue :
1
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
154824456
Full Text :
https://doi.org/10.1109/TGRS.2021.3097723