基于最小熵的SAR干扰图像配准与评估研究

Minimum entropy based registration strategy for airborne SAR images before and after noise jamming

噪声干扰前后SAR图像的有效配准是判断其受干扰程度、计算图像相关性的前提,也是开展SAR对抗效果评估的基本环节。针对SAR对抗试验中噪声干扰前后机载平台航次一致性难以精确保证的问题,提出了一种基于最小熵子域相关法的SAR干扰图像配准策略。首先,按照一定的搜索方法在干扰前后的SAR图像中进行相关子域选取;然后,按照最小熵准则进行SAR干扰图像配准;最后,分析推导了配准性能与受干扰程度之间的关系。仿真实例验证了该配准策略的有效性。

Effective registration of Synthetic Aperture Radar（ SAR） image before and after noise jamming is the basis for judging the jamming degree and for calculating image correlation, which is also a basis for evaluating the effect of SAR. We put forward a registration strategy for jammed images of SAR based on minimum entropy subfield correlation method. First, correlated subfields are selected in SAR images before and after jamming according to a certain search method; then the jammed images of SAR are registered based on minimum entropy principle; lastly, the relationship between the registration degree and the jamming degree is deduced and analyzed. Simulation showed the effectiveness of this strategy.