Under CopyrightWoock, P.P.Woock2022-03-1231.1.20132012https://publica.fraunhofer.de/handle/publica/37738310.1109/OCEANS-Yeosu.2012.6263449Navigation of a deep-sea autonomous underwater vehicle (AUV) is a difficult task in cases where no absolute positioning information (e.g., by long baseline systems) is available. Using inertial measurement sensors alone leads to accumulation of sensor noise and with it to corruption of position and orientation estimates over time. Simultaneous localization and mapping (SLAM) techniques can aid to limit the navigation error. In this paper it is discussed what type of features is suitable for sonar-based underwater navigation. For evaluation, a simulation environment has been created which performs environment shape reconstruction based on side-scan sonar data while additionally utilizing vehicular inertial measurement data (ego-motion). A ray-tracing based forward model creates a synthetic sonar response for a given elevation map and vehicle pose. Then, a pose-aware inversion method estimates an elevation map of the surrounding environment. This map is the basis for navigation. Therefore, the characteristics of the reconstruction method need to be taken into account for the feature design as well as the fact that the surface will be sampled differently upon a re-visit.en004conference paper