由于实波束地图方位分辨率低,从中很难分离出如机场、舰船及海岸线等目标的有用信息,使得战机无法实施对地、对海火力攻击。文中提出了一种基于实测数据处理的统计优化反卷积实波束锐化算法。该算法通过运动补偿及迭代算法,对实波束地图进行锐化,以实现方位超分辨。从仿真数据分析及实测数据处理的结果可以看出,所提方法能有效提高实波束地图的方位分辨率,具有很高的工程应用价值。 Due to the low azimuth resolution of real beam maps, it is very difficult to separate useful information such as the targets of airports, ships and coastlines, so that the fighter planes can not implement land-based and sea-fire attacks. In this paper, a statistical optimized deconvolution real beam sharpening algorithm based on measured data processing is proposed. The algorithm sharpens the real beam map by motion compensation and iterative algorithm to achieve azimuth super-resolution. From the simulation data analysis and the measured data processing results can be seen, the proposed method can effectively improve the azimuth resolution of the real beam map, with high engineering value.