A Multi-Beam Seafloor Constant False Alarm Detection Method Based on Weighted Element Averaging

Abstract

Due to the influence of environmental noise, sidelobe data, and tunnel emission under the background of multi-background underwater surveying and mapping, it is challenging to detect seafloor terrain in the background noise. Constant false alarm detection of seafloor terrain under the condition of constant false alarm probability has been an important research field. The constant false alarm detection can eliminate noise interference in a water body in the seabed topography mapping process and provide clear and accurate seabed topography information. Therefore, it is a challenging task to increase the detection probability, reduce the missing probability, and increase the detection speed in constant false alarm detection methods. Aiming at the shortcomings of the existing algorithms, this paper proposes an efficient weighted cell averaged constant false alarm detection method (WCA-CFAR). First, the cross-window reference unit sampling method is used to improve the detection speed and accurately sample the background noise unit. Then, the reference unit weighted average constant false alarm detection method is employed to calculate the detection threshold to achieve the purpose of target detection. The proposed method is verified by the simulation data detection test and a test on the actual lake test data. The test results show that the proposed method can effectively reduce the missing detection probability and improve the detection probability.

Keywords

• constant false alarm detection
• cross window
• multi-beam sonar