Fast two-dimensional censored mean level detector-statistics constant false alarm rate method for multi-beam seafloor terrain detection

Abstract

In order to solve the problem of false terrain caused by environmental interference and “tunneling effect” in conventional multi-beam seafloor terrain detection, this paper addresses a seafloor topography detection method based on fast two-dimensional (2D) CMLD-CFAR (censored mean level detector-Statistics Constant False Alarm Rate). A cross-sliding window is used in this method. The target occlusion phenomenon which occurs in multi-target environments can be eliminated by censoring the large cells of the reference cells, and the rest 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, which costs a lot of computational load. This paper proposes a fast algorithm with a global threshold to reduce the computational load. Only the regions of interest (ROI) which are selected by a global threshold will be detected by 2D CMLD-CFAR method, and the rest pixels are distinguished as clutters directly. The proposed method has been evaluated by the real multi-beam experimental data of which the background follows a distribution of Exponential. The results show that the novel method can effectively solve the problem of false terrain in multi-beam terrain survey and has a high detection accuracy.