目的掌握海上船舶分布状态对于海上交通流分析和通航安全管理具有重要作用。遥感技术,特别是星载合成孔径雷达(SAR)技术的发展,为大范围海上船舶检测提供了有效的手段,但受SAR成像机制影响,海上船舶目标在星载SAR影像上通常存在着不同程度的方位向模糊噪声,这些噪声易被误判为船舶,导致船舶识别中虚警率提高。方法本文简述了方位向模糊噪声的产生原因,提出了一种新的星载SAR影像上船舶方位向模糊去除算法,该算法的核心是构建目标方位向角度一致性、方位向位置偏移距离和方位向模糊能量衰减3个判别规则,对潜在SAR影像亮斑目标进行逐层筛选,实现船舶真实目标和方位向模糊目标的判别。结果选取中国渤海海域和黄海海域的30 m分辨率的Radarsat-2数据进行案例分析,并与船舶自动识别系统(AIS)实测数据进行比对校验,结果表明,传统的双参数恒虚警率(CFAR)算法和基于K分布的CFAR等算法对于船舶难以剔除方位向模糊,容易造成虚警,而本文算法对实验影像的船舶方位向模糊去除准确率优于95.8%,能够有效剔除船舶方位向模糊。结论该算法为星载SAR影像上船舶方位向模糊去除提供了新的手段,有助于提高SAR影像上船舶目标检测的准确性。 Objective To understand the distribution of ships at sea has an important role in maritime traffic flow analysis and navigation safety management. The development of remote sensing technology, especially the spaceborne synthetic aperture radar (SAR) technology, provides an effective means for the detection of large-scale marine vessels. However, due to the influence of SAR imaging mechanisms, the objectives of maritime vessels often vary in spaceborne SAR images to varying degrees The azimuth to the fuzzy noise, the noise is easily misjudged as a ship, resulting in false identification of ships to improve the rate of identification. This paper presents a brief description of the azimuthally induced blurring noise and proposes a new algorithm for ambiguous removal of ship azimuth based on spaceborne SAR images. The core of this algorithm is to construct the target azimuth and azimuth, And azimuth to the fuzzy energy attenuation three discriminant rules, the potential SAR image bright spot target screening layer by layer, to achieve the true goal of the ship and the azimuth to the fuzzy target discrimination. Results Radarsat-2 data with a resolution of 30 m in the Bohai Sea and Yellow Sea waters of China were selected for case analysis and verified with AIS data. The results show that the traditional two-parameter CFAR (CFAR) algorithm based on K distribution and CFAR algorithm based on K distribution are difficult to eliminate the azimuth ambiguity of the ship, which is easy to cause false alarm. The accuracy of this algorithm is better than 95.8% for removing azimuth from the experimental image, which can effectively eliminate the ship azimuth blurry. Conclusion This algorithm provides a new method for the ambiguous removal of ship azimuths from spaceborne SAR images and helps to improve the accuracy of ship target detection on SAR images.