Estimating the vertical offsets of a crowd-sourced bathymetry system using Kalman Filter solution
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Date
2025-03
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University of New Brunswick
Abstract
Crowd-sourced Bathymetry (CSB), recognized for its potential in mapping uncharted waters, is faced with credibility and useability concerns, which makes Hydrographic Offices (HOs) hesitant to consider them for use in
official nautical charts. This research implemented a Kalman Filter (KF) algorithm to estimate the vertical offsets between theGNSS receiver and the sonar and the GNSS receiver and the waterline, two quantities which are often not measured in a CSB system. The algorithm uses Ellipsoid Reference Survey (ERS) principles, estimated uncertainties, and hydrodynamic models for tidal adjustments. The solution was tested with six datasets collected from the Gulf of St. Lawrence where the difference between the previously estimated GNSS to sonar offset and the KF solution results ranged between -1.286m and 1.168m. The results showed the technique's ability to significantly improve CSB data quality by resolving these offsets, paving the way for wider adoption in official charts.