Performance Analysis Of CFAR And PDA Based Techniques For Tracking Of Point Moving Target In Heavy Clutter

In these years, because the demand of continuous improving the performance of military defense system makes people very interested in the technology of dim moving point target detection and tracking in long-range and low signal noise clutter ratio (SNCR), this subject becomes one of the research focus. In the condition of low signal noise clutter ratio (SNCR), dim moving point target detection and tracking is very important and challenging in area of image processing, remote sensing, radar monitor, robotics, and medial science etc.In this paper, the system principle of dim moving point target detection and tracking are first introduced, and then, the key technology, the advantages and disadvantages of different methods are proposed. On the principle that constant false alarm rate (CFAR), tracking algorithm for dim moving point target is described. After the discussion, PDAF tracking and PDAF-AI tracking are proposed, in the light of this two methods, the experiments are done, and experimental results are compared with each other. In the end, performance analysis is done.In order to observe the tracking performance of PDAF-AI and PDAF directly, Monte Carlo experiments are done, the results of experiment are consistent with theory, and the experimental result shows good results of algorithm proposed. Finally, summary and prospect are discussed.