基于局部最优匹配的斜视SAR子孔径成像算法

Local Optimal Matching Algorithm for Subaperture Imaging of Squint Synthetic Aperture Radar

斜视合成孔径雷达(Synthetic Aperture Radar,SAR)能够对雷达平台的侧前或侧后方区域进行观测,极大地增加了雷达的探测范围和灵活性。针对斜视SAR子孔径成像,该文提出一种基于局部最优匹配准则的成像算法。该算法在针对某方位频率构造对应的距离徙动校正、2次距离压缩以及方位补偿函数时,以"位于该方位频率处的点目标得到最佳匹配"为准则,不同于传统方法的以"方位中心点获得最佳匹配"为准则,从而能够避免距离方位中心较远的目标的失配,有效地改善了方位边缘区域的聚焦效果。文中通过点目标仿真验证了该算法的有效性。

Squint Synthetic Aperture Radar （SAR） can observe the side-front or side-rear scene of the platform. The squint mode improves the observation area and flexibility of SAR greatly. For subaperture imaging of squint SAR, a Local Optimal Matching Algorithm （LOMA） is proposed in this paper. In the algorithm, a new criterion is used in the presentation of the functions for range cell migration correction, secondary range compression and compensation in azimuth frequency domain. The criterion is that the target located at the azimuth frequency is matched optimally. It is different from the traditional algorithm, whose criterion is that the target at the azimuth center is matched optimally. Based on the new criterion, the proposed algorithm is able to avoid the mismatching and improve the focusing of the targets far from the azimuth center. The validity of the proposed algorithm is illustrated by the simulation results.