基于外推陷波滤波的孤立强散射旁瓣抑制
Sidelobe suppression of isolated strong scatterers based on extrapolated notch filtering

为了有效抑制极化合成孔径雷达(SAR)图像中的孤立强散射旁瓣, 并同时保持图像统计特性和极化散射特性, 提出了一种基于二维外推陷波滤波的孤立强散射旁瓣抑制的方法。该方法首先运用Chirp-Z变换进行AR(1)模型参数辨识, 并在此基础上推导得到了基于稳态Kalman预测理论的数据外推公式; 然后, 运用线性相位等波纹陷波滤波器实现强散射信号滤除; 最后, 在频域还原强散射信号主瓣, 并精确补偿滤波时引入的图像幅度误差。不同于空间变迹法和自适应旁瓣抑制方法, 该方法处理过程简单, 且有效保持了图像分辨率、图像统计特性和极化散射特性。仿真和实测数据处理验证了该方法的有效性。
Abstract：A two-dimensional extrapolated notch filtering method was developed to suppress sidelobes due to isolated strong scatterers in polarimetric synthetic aperture radar (SAR) images and to maintain the statistical and polarization scattering characteristics. A Chirp-Z transform is used for the AR(1) parameter identification with two-dimensional signal extrapolation based on steady-state Kalman prediction theory. The strong scatterer signals are eliminated by filtering the extrapolated signal with a linear-phase equiripple notch filter. The mainlobes of the strong scatterer signals are recovered in the frequency domain and the image amplitude error is accurately compensated in the filtering process. Unlike both spatially variant apodization (SVA) and adaptive sidelobe suppression (ASS), this method preserves the image resolution, the statistics and the polarization scattering characteristics with a simpler procedure. The effectiveness of this method is demonstrated by simulated and real data.