  Accurate, self-consistent bathymetric maps are needed to monitor changes in
subsea environments and infrastructure. These maps are increasingly collected
by underwater vehicles, and mapping requires an accurate vehicle navigation
solution. Commercial off-the-shelf (COTS) navigation solutions for underwater
vehicles often rely on external acoustic sensors for localization, however
survey-grade acoustic sensors are expensive to deploy and limit the range of
the vehicle. Techniques from the field of simultaneous localization and
mapping, particularly loop closures, can improve the quality of the navigation
solution over dead-reckoning, but are difficult to integrate into COTS
navigation systems. This work presents a method to improve the self-consistency
of bathymetric maps by smoothly integrating loop-closure measurements into the
state estimate produced by a commercial subsea navigation system. Integration
is done using a white-noise-on-acceleration motion prior, without access to raw
sensor measurements or proprietary models. Improvements in map self-consistency
are shown for both simulated and experimental datasets, including a 3D scan of
an underwater shipwreck in Wiarton, Ontario, Canada.
