Fast Double Selectivity Index-CFAR Detection Method for the Multi-Beam Echo Sounder

Abstract

Seafloor terrain and water column target detection is of great significance in marine surveys. However, the complex clutter environment can dramatically affect the detection performance of a multi-beam echo sounder. To simultaneously and robustly detect the seafloor terrains and water column targets, this paper proposes a fast two-dimensional double selectivity index-constant false alarm rate (DSI-CFAR) detection method. A two-dimensional cross sliding window, which includes reference cells and guard cells, is used in this paper. The proposed method improves the detection performance by using the appropriate clutter power level estimation strategies in different directions. An exponential model is accurately built by fitting various distributions, so the DSI-CFAR detection performance is greatly ameliorated. To reduce the computational load of the method, this paper uses a fast algorithm based on the global threshold. The region of interest (ROI) is selected by the preset global threshold, and the DSI-CFAR detector is only performed in the region of interest, which significantly reduces the number of pixels that must be calculated. In this paper, the measured results of different sliding windows and CFAR detection methods validate the basic performance of the proposed method.

Keywords:

• seafloor terrain and water column target detection
• probability of false alarm
• fast CFAR algorithm
• sonar imagery

Acknowledgement

This research was funded by the National Key R&D Program of China (grant number 2017YFC0306000 and 2016YFC1402303), the National Natural Science Foundation of China (grant number U1809212, U1709203 and 41576102).

Additional information

Funding

This research was funded by the National Key R&D Program of China (grant number 2017YFC0306000 and 2016YFC1402303), the National Natural Science Foundation of China (grant number U1809212, U1709203 and 41576102).