In order to solve the problem of false terrains caused by environmental interferences and tunneling effect in the conventional multi-beam seafloor terrain detection, this paper proposed a seafloor topography detection method based on fast two-dimensional (2D) Censored Mean Level Detector-statistics Constant False Alarm Rate (CMLD-CFAR) method. The proposed method uses s cross-sliding window. The target occlusion phenomenon that occurs in multi-target environments can be eliminated by censoring some of the large cells of the reference cells, while the remaining reference cells are used to calculate the local threshold. The conventional 2D CMLD-CFAR methods need to estimate the background clutter power level for every pixel, thus increasing the computational burden significantly. In order to overcome this limitation, the proposed method uses a fast algorithm to select the Regions of Interest (ROI) based on a global threshold, while the rest pixels are distinguished as clutter directly. The proposed method is verified by experiments with real multi-beam data. The results show that the proposed method can effectively solve the problem of false terrain in a multi-beam terrain survey and achieve a high detection accuracy.

为了解决传统的多波束海底地形检测中环境干扰和隧道效应造成的假地形问题，提出了一种基于快速二维（2D）删失均值检测器统计常数的海底地形检测方法。错误警报率（CMLD-CFAR）方法。所提出的方法使用s的横向滑动窗口。可以通过检查参考单元格的一些大单元格来消除多目标环境中发生的目标遮挡现象，而其余参考单元格则用于计算局部阈值。常规的2D CMLD-CFAR方法需要估计每个像素的背景杂波功率电平，从而显着增加了计算负担。为了克服此限制，提出的方法使用快速算法根据全局阈值选择感兴趣区域（ROI），而将其余像素直接区分为杂波。通过实际的多光束数据实验验证了该方法的有效性。结果表明，该方法可以有效解决多波束地形测量中的假地形问题，并具有较高的检测精度。