Abstract: For the data characteristics of interferometric multi-beam echo sounder (MBES), a single ping filtering method of MBES based on dynamic clustering is proposed. Considering the continuity of real terrain, the problem of outlier detection is transformed into clustering of real terrain data. Through continuous clustering of real terrain data, the outliers in data are eliminated. For the large data size in the process of clustering, dynamic clustering is adopted after partitioning clustering sets. Simultaneously, a trend adjusted factor is introduced for the feature domain selection, which is helpful for the decision of clustering direction. At last, the improved k-means method is utilized for output of clustering object. The results from processing sea test data of GeoSwath MBES show that the algorithm has good adaptability for different terrain characteristics, and is simple for implementation, which can be used for real-time filtering and post-processing of MBES data.

Key words: multi-beam echo sounder, dynamic clustering, feature domain, k-means method