Advancing a Design for Trusted Community Bathymetry

TitleAdvancing a Design for Trusted Community Bathymetry
Publication TypeThesis
Year2023
AuthorsTauriello, D
Degree and ProgramEarth Science: Ocean Mapping
DegreeMaster of Science
Number of Pages100
Date PublishedApril 2023
UniversityUniversity of New Hampshire
LocationDurham, NH

The design for a Trusted Community Bathymetry (TCB) system, presented in Calder et al., 2020, demonstrates a data collection system capable of collecting precisely geo-referenced depth soundings from any navigational echosounder installed on a volunteer vessel. The TCB system is capable of autonomously determining any vertical installation offset with respect to the waterline, and provides sufficient guarantees of data quality to allow the soundings to be considered for hydrographic use.

This thesis presents two contributions to advance the original TCB system design. First, it capitalizes on the widespread availability of low-cost sidescan modules in the recreational sonar market by describing a method to integrate one of these units with the existing TCB datalogger. This integration adds significant richness to a volunteer dataset by enabling a hydrographic office to benefit from imagery of targets and obstructions in the vicinity of TCB vessels. Additionally, a method for autonomous operation is presented in which the TCB datalogger may command the sidescan to automatically log imagery in the vicinity of targets of interest specified by the hydrographic office.

Second, this work demonstrates it is possible to replace the survey-grade GNSS receiver antenna used in the original system design with a comparatively inexpensive unit. The replacement antenna does not provide equivalent real-time performance but can collect observations which can be post-processed to produce solutions with uncertainties on the same order as the survey-grade antenna. Since real-time performance is not important in a TCB application, this development represents a significant reduction in total system cost and increases the viability of widespread deployment without sacrificing data quality.