CS算法结合COAA算法提高机载合成孔径雷达成像质量

该文将对比度最优自聚焦算法(COAA)与基本Chirp Scaling算法(CSA)相结合，对CS算法方位处理过程做适当变化，把COAA算法融入其中，一方面进行精确的无插值距离徙动校正，一方面进行准确的二次相位误差估计和校正，从而提高机载合成孔径雷达的成像质量。通过对COAA算法采用变步长迭代提高二次相位误差估计的精度和速度，增强算法的实用性。文中给出两种算法相结合进行雷达数据成像处理的流程图，并用条带正侧视SAR模式实际雷达数据验证研究结果的有效性。

Chirp Scaling Algorithm Integrated with COAA to Improve Airborne SAR Image Quality

Chirp Scaling Algorithm (CSA) is integrated with Contrast Optimization Autofocus Algorithm (COAA) via properly modifying azimuth processing of CS to incorporate COAA in it, resulting in improving airborne SAR image quality. RCMC is precisely corrected by means of CSA without interpolation, on the other hand, precise estimation and correction for the second phase error in SAR raw data is accomplished. To improve the phase error estimation precision and speed, modified iteration step is used, resulting in more effective application of COAA. In this paper, the SAR processing flow diagram of the two integrated algorithms is given. Finally, the effective experimental results are shown with real stripmap broadside SAR data.