基于小批量K均值预分类的多波束反向散射强度角度影响改正

Correction of multi-beam backscatter intensity angle based on Mini Batch K-means pre-classification

角度响应变化是影响多波束声呐回波图像质量的主要因素,为了后续利用多波束反向散射图像进行海底底质分类,需去除角度响应的影响。国内外已开展角度响应模型及改进模型研究,但现有方法很难适应复杂海底底质环境。针对此问题,通过小批量K均值聚类将测区海底点预分为高阻抗平滑底质和低阻抗粗糙底质,然后构建自适应改正模型逐测线去除角度响应的影响。实验选用浙江海域实测4条相邻测线数据,采用Lambert模型法、二次微分法和本文方法分别进行了反向散射强度角度影响去除。本方法处理后角度响应去除效果最佳(MIC=0.123);在多波束条带重叠区,反向散射强度标准差为1.46 dB,有效改善了复杂底质环境下的多波束声呐图像质量。

Angular response is the major factor that affects the quality of multi-beam echo sonar image.In order to classify seafloor sediment according to the multi-beam backscatter images,the influence of angular response need to be removed.Research on angular response model and improved model has been carried out at home and abroad,but few existing methods can adapt to the complex seabed sediment environment.In order to solve this problem,mini batch K-means clustering was used to classify the seafloor points into high impedance smooth sediment and low impedance rough sediment.Afterwards,an adaptive correction model was constructed to remove the influence of the angular response line by line.In the experiment based on the data obtained from four adjacent measuring lines in the sea area of Zhejiang province,the Lambert model method,the quadratic differential method and the proposed method were used to remove the influence of the angle of backscattering intensity.The angular response removal effect of this algorithm is best when maximal information coefficient(MIC)is equal to 0.123.In the overlapping region of multi-beam strips,the standard deviation of backscatter intensity is 1.46 dB and the image quality of multi-beam sonar in complex substrate environment is improved effectively.