复杂应用条件下的BFSAR时域快速成像及自聚焦误差补偿技术研究

双基前视SAR（BFSAR）成像技术已在越来越多的领域体现出重要的应用潜力。在诸多复杂的应用条件下，由于雷达平台构型和运动轨迹特殊，BFSAR回波信号不再满足方位不变的假设，给现有频域成像算法的应用增加困难，而采用时域成像具有其特有的优势。本课题针对BFSAR时域快速成像和时域自聚焦中的关键问题展开研究：1）利用波数矢量分解找到子图像的频谱解析表示，以此研究基于椭圆正交极坐标系的BFSAR时域快速成像算法，提高处理效率；2）确立相位误差和NsRCM的相互关系，研究相位误差和NsRCM联合补偿的自聚焦处理方法，提高误差补偿精度；3）建立估计误差在相位历程域和空间域的对应关系，并利用误差在空间域的连续特性，研究估计误差预处理方法，消除图像融合引入的图像不连续，实现BFSAR的快速连续成像。预期得到一套稳健有效的时域快速成像方法，为BFSAR在工程上更好地实现时域快速成像提供理论依据和算法基础。

Bistatic forward-looking synthetic aperture radar (BFSAR) has significant potential in more and more practical applications. For many practical applications under severe conditions, the complex geometry as well as the irregular trajectory make the assumption of azimuth-invariant of BFSAR echoes no longer valid, which brings difficulties in the design of conventional frequency-domain algorithm. For BFSAR imaging under complex conditions, the time-domain algorithm has its unique advantages. This new project will study on the key issues of fast time-domain algorithms as well as time-domain autofocusing techniques for BFSAR imaging: 1) Based on the wavenumber decomposition technique and orthogonal elliptical polar coordinate system, a new fast time-domain algorithm with higher efficiency will be studied; 2) By establishing the relationship between phase error and nonsystematic range cell migration (NsRCM), a joint autofocusing strategy will be studied to improve the accuracy of error estimation; 3) By exploring the connection of estimated error between phase history domain and spatial domain, as well as the continuity of phase error in spatial domain, a preprocessing technique for error estimation will be studied to remove the discontinuity of image, so that the fast time-domain processing for BFSAR continue imaging can be well realized. Through the research achievements in this project, a practical approach for BFSAR data processing with robustness and high-efficiency will be obtained, which will also provide theoretical and algorithmic foundations of fast time-domain processing for practical BFSAR imaging.