Simulation of Sea Clutter Data Based on DPOS-CFAR Detection Algorithm

The classical Log-t-CFAR dual parameter detector has CFAR performance for both scale parameters and shape parameters. Compared with the single parameter CFAR detector, it has stronger clutter adaptability, but there are some problems, such as large false alarm loss and a large amount of computation. In this paper, feedback control is applied to CFAR detection. Based on OS-CFAR, a dual parameter ordered statistics (DPOS) CFAR detector with feedback control is proposed, which solves the problem of large false alarm loss of dual parameter CFAR detector. Its performance is analyzed and verified by actual sea clutter data simulation. The simulation results show that the detection performance of the DPOS-CFAR detector is better than that of the classical dual parameter detector.