In order to robustly perform SLAM (Simultaneous Localization
and Mapping), places need to be recognized when they are visited again.
In the deep-sea environment SLAM-assisted navigation based on side-scan
sonar data benefits from using three-dimensional features of the environment
as they are much less view-dependent than classic 2D features. Obtaining
these features requires processing of the sonar data as the side-scan
sonar sensor readings contain three dimensional information only indirectly.
To extract that information the ensonification process needs to be inverted.
This inversion is an ill-posed inverse problem and therefore regularization is
needed before a unique solution can be found. Once the true seabed shape is
reconstructed, wide area SLAM techniques can be applied.