Knowledge of offset vectors from sonars, mounted on vessels, to systems such as Inertial Measurement Units (IMUs) and Global Navigation Satellite Systems (GNSS) is crucial for accurate ocean mapping applications. Traditional survey methods, such as employing laser scanners or total stations, are used to determine professional vessel offset distances reliably. However, for vessels of opportunity that are collecting volunteer bathymetric data, it is beneficial to consider survey methods that are less time consuming, less expensive, and which do not involve bringing the vessel into a dry dock. Thus, this thesis explores three alternative methods that meet this criterion for horizontally calibrating vessels
With the development of Unmanned Aircraft Systems (UASs) in the field of mapping, more cost-effective and quicker surveys can be conducted. For standard mapping applications, the tradeoff in using UASs compared to traditional surveying instruments is that there is an increase in errors. To investigate the potential of using UASs to accurately calibrate horizontal vessel offsets, UASs were utilized to calibrate a vessel with both Structure from Motion (SfM) photogrammetry and aerial lidar while the vessel was moored. Estimates of the horizontal deviations from ground truth, for both methods, were obtained by comparing the horizontal distances between targets on a vessel, acquired by the UAS methods, to ground-truth measurements of offset distances from survey-grade laser scanning of the vessel. In addition to the UAS methods, a seafloor reference technique that involves collecting single-beam echo sounder (SBES) data over a known bathymetric feature to estimate horizontal offsets of a vessel, was investigated.
Errors for the seafloor reference method were on the meter level and therefore may only be relevant for larger offsets such as on larger ships. In contrast, UAS methods were able to achieve horizontal deviations on the order of centimeters with the use of Ground Control Points (GCPs).
|Commitee:||Dijkstra, Semme, Parrish, Christopher|
|School:||University of New Hampshire|
|School Location:||United States -- New Hampshire|
|Source:||MAI 81/12(E), Masters Abstracts International|
|Subjects:||Remote sensing, Ocean engineering|
|Keywords:||Hydrography, Mapping, Surveying, UAS|
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