【摘要】 极化合成孔径雷达(PolSAR)具有全天候全天时工作的优势,其目标结构、目标指向以及目标组成等参数与极化散射机理有着密切的联系,提供了相比单极化更加丰富的目标信息。因此,利用PolSAR图像可以更完整地揭示目标信息和物理属性,更适合于目标的检测与识别。针对复杂陆地环境下PolSAR典型人造目标识别需求,提出了基于广义Gamma分布的双尺度CFAR目标检测算法,在此基础上基于极化特征进行目标鉴别,并利用机载极化SAR飞行试验数据进行了算法验证,实验结果表明,所提算法可有效降低虚警率,实现对复杂陆地环境下极化SAR典型人造目标的有效检测。更多还原

【Abstract】 The polarimetric synthetic aperture radar( PolSAR) has such advantages as all-weather and all-time operation,its target structure,target pointing and composition have close relation with the polarization scattering principle,and it can provide richer target information,compared with single polarization.The PolSAR images can be used to obtain complete target information and physical behavior,and they are convenient for target detection and recognition. Aiming at the great demands for recognition of typical artificial targets under complex terrestrial environment,this paper proposes a two-scale CFAR target detection algorithm based on generalized Gamma distribution,and the target discrimination is implemented based on polarimetric features.The proposed algorithm is demonstrated by using airborne polarimetric SAR flight experiment data. The experimental results show that the proposed algorithm can significantly reduce the false alarm rate,and implement effective detection of polarimetric SAR man-made target in complex terrestrial environment.更多还原