Automatic detection of punctual errors in multibeam data using a robust estimator

The Oceanographic and Hydrographic service of the Navy (SHOM) has been usin g two MultiBeam Echo-Sounders (MBES) since 1988. These systems enable swath coverage of the sea floor along a survey line. Compared with single beam Echo-sounder systems, the resolution of the data provided by these systems has been considerably increased. Nevertheless, er rors still remain and they must be detected and eliminated to meet the inte rnational standards of bathymetric charts. The high volume of data, particularly in the case of very shallow water Ech o-Sounder systems, makes manual validation of the data inappropriate. In or der to reduce the operating costs of the data cleaning step, SHOM has devel oped algorithms to automatically detect huge datasets generated by MultiBea ms. The algorithm described in this paper is based on a local modelization of t he seabed. The fitting of a quadratic surface over the raw data is carried out using a robust estimator. We retained Tukey robust estimator as the mos t effective choice due to its adaptative capabilities. Possible outliers ar e soundings with high residual values between measured depths and depths es timated from the local model. Retained outliers are deduced from this first outliers set, by computing local cross validation. This algorithm has been tested on different bathymetric data sets. Its effi ciency has been demonstrated whatever the depth or type of seabed. Moreover , its application only requires two parameters to be set, thus making it th e obvious choice. It has currently been adopted and installed on board all the SHOM's ships.