Interpolation of bathymetry data from the Sea of Galilee: A noise attenuation problem

We process a bathymetry survey from the Sea of Galilee. This data set is contaminated with non-Gaussian noise in the form of spikes inside the lake and at the track ends. There is drift on the depth measurements leading to vessel tracks in the preliminary depth images. The drift comes from different seasonal and human conditions during data acquisition, e.g., wind and water levels. We derive an inversion scheme that produces a much-reduced noise map of the Sea of Galilee. This inversion scheme includes preconditioning and iteratively reweighted least squares with the proper weighting function to remove the non-Gaussian noise. We remove the ship tracks by adding a modeling operator inside the inversion that accounts for the drift in the data. We then approximate the model covariance matrix with a prediction error filter that enhances details inside the lake. Unfortunately, the prediction error filter slightly degrades the frequency content of the final depth map. Our images of the Sea of Galilee show ancient shorelines and, inside the lake, rifting features.