In this contribution a method for correcting bathymetric measurements affected by inaccurate water column sound speed profiles (SSPs) is presented. The method exploits the redundancy in the multibeam echosounder measurements obtained from the overlap of adjacent swaths by minimizing the difference between depths along overlapping swaths. Two optimization methods are used, i.e., Differential Evolution (DE) and Gauss-Newton (GN). While DE inverts for the sound speed by minimizing the depth variation, GN inverts for both bathymetry and sound speed by minimizing the squared sum of the differences between the modeled and measured travel times. The inversion method assumes a constant SSP in the water column. Applying the method to a salt wedge survey area with large variations in the water column sound speed indicates a good agreement between the original depth measurements and those derived after the inversion with the mean and standard deviation of the depth differences equaling 0.009m and 0.024m, respectively. This indicates that even with a simple parametrization of the sound speed in the water column, the correct bathymetry can be derived from the inversion. The SSP inversion method is also applied to an area with existing refraction artefacts. It corrects the bathymetry and reduces the mean and standard deviation of the depth standard deviation by a factor of around 2.75 compared to the case where the measured SSPs were used. Furthermore, the SSP inversion method neither manipulates the existing morphology nor introduces artificial bathymetric features in the areas where such refraction artefacts are not present. Considering constant SSPs, both DE and GN give almost identical results with GN being faster. However, GN is less flexible with regards to varying sound speed parameterizations.

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In a world of high precision sensors, one of the few remaining challenges in multibeam echosounding is that of refraction-based uncertainty. A poor understanding of oceanographic variability or a poor choice of equipment can lead directly to poor quality bathymetric data. Post-processing software tools have existed for some time to allow data processors to correct for these artifacts. These tools typically involve the manual review of soundings and manual adjustment of a small set of parameters to achieve the desired correction. Though there are a number of commercial solutions currently available, they all have the same inherent weaknesses: (1) they are manual, thus time-consuming, (2) they are subjective, thus not repeatable, (3) they require expert training and thus are typically only usable by experienced personnel. QPS and the Technical University of Delft, The Netherlands (TU Delft) have worked together to implement an algorithm to address these issues in QPS’ post-processing software, Qimera. The algorithm, the TU Delft Sound Speed Inversion, works by taking advantage of the overlap between survey lines, harnessing the power of redundancy of the multiple observations. For a given set of pings, the algorithm simultaneously estimates sound speed corrections for the chosen pings and their neighbors by computing a best-fit solution that minimizes the mismatch in the areas of overlap between lines. This process is repeated across the entire spatial area, allowing for an adaptive solution that responds to changes in oceanographic conditions. This process is completely automated and requires no operator interaction or data review. The algorithm is also physics-based in that it honors the physics of acoustic ray bending. For accountability, the algorithm preserves the output of the inversion process for review, vetting, adjustment, and reporting. In this paper, we briefly explain how the algorithm works in simple terms. We also explore two data sets that cover differing oceanographic conditions, seabed morphologies, and survey line planning geometries in order to establish some early guiding principles on how far the algorithm can be pushed for performance. @en