This thesis demonstrates, that bathymetric data improves data imaging results of full wavefield migration using different acquisition designs. The algorithm gets more stable by constraining the inversion with the sea bottom information, especially in case of large source and receiver spacings, without making compromises on image quality. Not using the proposed method will result in uninterpretable images, if the topography of the seafloor gets too complex.
In this thesis it is proposed to use an autonomous underwater vehicle (AUV) to acquire the bathymetry. The quality of the bathymetry is highly dependent on the ability to adequately localize the AUV. Therefore a terrain based navigation system was developed based on Kalman filters. It is shown that using a Kalman filter combined with sparsely sampled sea bottom information was of advantage to locate the vehicle at its true position. This is not possible with just using the inertial navigation system of the AUV.