基于动态聚类的单声脉冲多波束测深数据滤波

摘要

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.%针对相干型多波束测深数据的特点，提出了一种基于动态聚类的单声脉冲多波束测深数据实时滤波算法。利用地形的连续性特性，将测深数据的异常值检测问题转化为真实地形的聚类问题，通过不断地聚类提取真实的地形数据，对异常值进行剔除。在聚类过程中，由于数据量很大，对聚类集合进行划分后采用动态聚类的方式，同时引入地形趋势变化调节因子，选定地形特征域，对聚类的方向进行判断，最后利用改进后的 k 均值法进行聚类目标输出。对 GeoSwath 多波束测深系统的真实海上试验数据的处理结果表明，该算法对地形特征具有较强的适应能力，且实现简单，可用于多波束的在线滤波以及测深数据的后处理。