Robust Automatic Reduction of Multibeam Bathymetric Data Based on M-estimators

Multibeam echosounders have commonly been employed for a wide range of applications including offshore survey, navigation, hydrogeology, and oceanography. Because the tremendous volume of the bathymetric data is demanding for some purposes and requires significant storage space, the data reduction plays a prominent role in practice. Additionally, the multibeam soundings are inevitably contaminated with sporadic outliers, and as such, the data cleaning can be challenging especially in shallow waters. We present a speedily robust method for reliably reducing the volume of the bathymetric data within grid cells. In this respect, robust M-estimators are recursively applied to the data in a patch-wise manner to alleviate the undesirable effects of the outlying observations. Accordingly, the reduced bathymetry is automatically made unaffected by the possible outliers once their equivalent weights have been downweighted. The performance of the presented method has been demonstrated by synthetic datasets and an experimental dataset collected by an ATLAS FS 20/100 kHz shallow-water multibeam echosounder in the offshore waters of Kish wharf. The reliability, efficiency, and capability of the proposed method have been verified, which makes it quite possible to meet the IHO requirements for special-order seafloor mapping.