Automated error detection in multibeam bathymetry data

For a variety of reasons, multibeam swath sounding systems produce errors that can seriously corrupt navigational charts. To address this problem, the authors have developed two algorithms for identifying subtle outlier errors in a variety of multibeam systems. The first algorithm treats the swath as a sequence of images. The algorithm is based on robust estimation of autoregressive (AR) model parameters. The second algorithm is based on energy minimization techniques. The data are represented by a weak-membrane or thin-plate model, and a global optimization procedure is used to find a stable surface shape. Both of these algorithms have undergone extensive testing at bathymetric processing centers to assess performance. The algorithms were found to have a probability of detection high enough to be useful and a false-alarm rate that does not significantly degrade the data quality. The resulting software is currently being used both at processing centers and at sea as an aid to bathymetric data processors