Research Of Clutter Suppression Algorithm For Marine Navigation Radar And Implementation Of Constant False Alarm Rate Detection Based On FPGA

Targets detection under the background of sea clutter is a research focus in the field of radar signal processing. Especially in the case of variable sea area environment, the sea clutter is fickle, resulting in the complexity of radar echo signal. It seriously hampers the detection of targets on the sea surface. Therefore, sea clutter suppression technique is the key factor for improvement of targets detection above the sea surface. In this paper, based on the problems above, the main work and innovations of the related research are as follows:(1) This paper firstly analyzes the statistical characteristic of sea clutter. Several classic amplitude distribution models of sea clutter are described, as well as the power spectrum characteristic of sea clutter. Then, the methods of sea clutter simulation are introduced and models of sea clutter are subsequently simulated. Based on the theories mentioned above, a sea clutter suppression algorithm of marine navigation radar via statistical multi-model is proposed. According to the characteristics of multi-scanning radar echo, corresponding parameters of each model in model library are estimated statistical. Compared with the distribution curve of the radar echoes, the optimal matched model is applied to sea clutter suppression via cancellation, which suppresses the interference of the sea clutter. Simulation and analysis of the measured data show that the method can effectively suppress sea clutter.(2) This paper studies the Constant False Alarm Rate (CFAR) algorithm under sea clutter. Firstly, the paper introduces the basic theory of CFAR detection techniques and three kinds of Mean Level-Constant False Alarm Rate (ML-CFAR) methods and ordered statistics target detection algorithm (OS-CFAR, OSGO-CFAR). Detection performance of a variety of CFAR processing methods in uniform clutter background is analyzed, as well as that in clutter background of multi interfering targets and the background of clutter edge. Via analysis of the simulation results, it is indicated that that OSGO-CFAR algorithm has better detection performance.(3) In this paper, ML-CFAR, OSGO-CFAR algorithm were designed and implemented based on FPGA. In the design process, OSGO-CFAR detector was optimized to reduce the computations and resource depletion. The correctness and feasibility of the algorithm design were verified by the simulation results and resource utilization.