Track Detection of Underwater Moving Targets Based on CFAR

Abstract In this paper, we propose a 2D-Weibull-Constant False Alarm Rate (2D-Weibull-CFAR) detection algorithm to solve the problem that detecting current underwater targets is difficult due influence of reverberation noise. Specifically, referring idea CFAR uses probability distribution reference units detect objects, paper introduces pixel noise into detector. After that, extracted estimated, and then adaptive threshold obtained achieve reliable targets. Finally, Hough transform extracts trajectory results. The experimental test shows in can false alarms missed hidden effectively target results show has higher accuracy lower alarm rate than comparison algorithm.