| 基于先验相位结构信息的双基SAR两维自聚焦算法 |
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| 引用本文： | 施天玥,刘惠欣,刘衍琦,毛新华.基于先验相位结构信息的双基SAR两维自聚焦算法[J].雷达学报,2020,9(6):1045-1055. |
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| 作者姓名： | 施天玥 刘惠欣 刘衍琦 毛新华 |
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| 作者单位： | 南京航空航天大学电子信息工程学院雷达成像与微波光子技术教育部重点实验室 南京 211106 |
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| 基金项目： | 创新基地(实验室)开放基金;优秀青年科学基金;国家自然科学基金 |
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| 摘 要： | 两维自聚焦是高机动条件下机载合成孔径雷达(SAR)高分辨率成像的重要保障。现有的双基SAR两维自聚焦算法没有充分利用相位误差的先验结构信息，是对相位误差的一种盲估计，在计算效率和参数估计精度方面仍然存在很大限制。该文从双基SAR极坐标格式成像算法新解释入手，从残留距离徙动(RCM)校正的观点出发，将极坐标格式(PFA)算法的实现解释为距离频率和方位时间两个变量的解耦过程。利用这一观点分析了极坐标格式算法中的距离和方位重采样对两维相位误差的影响，揭示了残留两维相位误差固有的解析结构。基于这一固有的先验信息，该文提出了一种结合先验信息和图像数据的双基SAR两维自聚焦算法。算法通过引入先验知识，将两维相位误差估计降维成一维方位相位误差的估计；同时，在估计方位相位误差时，通过多子带数据平均，充分挖掘了所有数据的信息。相比于已有算法，无论是参数估计精度还是计算效率都有明显改善。实验结果验证了该文理论分析的正确性以及所提两维自聚焦方法的有效性。
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| 关 键 词： | 合成孔径雷达 双基雷达 极坐标格式算法 两维自聚焦 先验知识 |
| 收稿时间： | 2020-04-24 |
Bistatic Synthetic Aperture Radar Two-dimensional Autofocus Approach Based on Prior Knowledge on Phase Structure |
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| SHI Tianyue,LIU Huixin,LIU Yanqi,MAO Xinhua.Bistatic Synthetic Aperture Radar Two-dimensional Autofocus Approach Based on Prior Knowledge on Phase Structure[J].Journal of Radars,2020,9(6):1045-1055. |
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| Authors: | SHI Tianyue LIU Huixin LIU Yanqi MAO Xinhua |
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| Affiliation: | Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China |
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| Abstract: | Two-Dimensional (2-D) autofocus is an important guarantee for high-resolution imaging of airborne Synthetic Aperture Radar (SAR) under high maneuvering conditions. The existing 2-D autofocus approaches for bistatic SAR blindly estimate the phase error and do not fully utilize the prior knowledge on phase structure. In this paper, a new interpretation of the Polar Format Algorithm (PFA) for general bistatic SAR imaging is presented. From the viewpoint of Residual Cell Migration (RCM), PFA is converted into 2-D decoupling. By utilizing this new formulation, we analyze the effect of range and azimuth resampling on the residual 2-D phase error and reveal the inherent structure characteristics of the residual 2-D phase error in the wavenumber domain. The 2-D phase error estimation can reduce to one dimensional azimuth phase error estimation. Based on this prior knowledge, a structure-aided 2-D autofocus approach is proposed. Meanwhile, the information of all the data is fully excavated by averaging sub-band data when the azimuth phase error is being estimated. Compared with the existing algorithms, both the parameter estimation precision and computational efficiency are significantly improved. Experimental results clearly demonstrate the correctness of the theoretical analysis and the effectiveness of the proposed method. |
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