基于改进PGA算法的机载条带式UWB SAR运动误差精补偿

Fine Motion Compensation for Airborne Stripmap UWB SAR Based on Improved PGA

传感器精度较低的情况下,单纯基于测量数据的运动补偿难以满足机载超宽带合成孔径雷达(UWB SAR)的聚焦精度,需要自聚焦算法对初步聚焦的图像进行精补偿。相位梯度自聚焦(PGA)是一种高效、稳健的自聚焦算法。文中研究了PGA算法在机载条带式UWB SAR中的应用,提出一种改进的三步选点策略以提高选点质量,然后对基于参考点对齐的子图像拼接方法进行了改进。实测P波段机载UWB SAR数据处理结果表明改进PGA算法精度高、收敛快,可有效校正残余相位误差,并完成较高精度的子图像拼接。

When the accuracy of the motion sensor is low,the sensor-based Motion compensation( MoCo) can not gain enough accuracy for airborne Ultra-wide Band Synthetic Aperture Radar( UWB SAR),so the autofocus algorithm is needed to carry out the fine MoCo for the primary focused image. The Phase Gradient Autofocus( PGA) is an algorithm with high efficiency and robustness. In this paper,the application of the PGA algorithm in the airborne stripmap UWB SAR is studied and a three-step scatter-selection strategy is proposed to improve the quality of the selected scatter,then the reference scatter coregistration method is improved to concatenate the sub-image. The processing results of the real data from a P band airborne UWB SAR shows that the improved PGA algorithm has high accuracy and convergence speed,it can be used to correct the residual phase errors effectively and accomplish high-precision sub-image mosaicing.