基于两步方位重采样的中轨SAR聚焦方法

中轨轨道显著的弯曲特性导致中轨SAR信号存在2维空变，因此大场景成像对于中轨SAR仍然是个难题。该文使用参数2维空变的4阶多项式模型对信号进行建模。同时提出一种基于两步方位插值的信号方位空变校正方法，通过方位时域重采样可以校正参考距离上不同方位目标点的多普勒调频率的线性和2次空变，距离向利用CS/RMA算法即可校正场景中所有点目标的距离徙动，而第2步多普勒重采样则能够校正剩余的多普勒参数的空变特性，包括剩余的距离方位耦合空变，以及高阶多普勒参数空变。通过两步插值法能够完全校正整个场景目标信号的方位空变特性，使得传统频域成像算法可以应用于中轨SAR的大场景聚焦。最后通过所提方法与参考方法的仿真结果对比，验证了所提方法的有效性。

Medium-earth-orbit SAR Data Focusing Method Based on Two-step Azimuth Resampling

The obvious orbit curvature of Medium Earth Orbit (MEO) results in severe two-dimensional space variance in the received signals. Thus, the focusing of MEO SAR data is still a problem to be solved. Fourth-order polynomial is used to model the range history. Also, an azimuth two-step resampling method is proposed to address the azimuth variance. The azimuth resampling in the time domain can adjust the azimuth chirp rate to be the same, then CS/RMA algorithm can be used to handle the space variance of the RCM. The second-step azimuth resampling can correct the left space variance of the Doppler parameters, including range-azimuth coupled space variance of the azimuth chirp rate, and the higher-order focusing parameters. The proposed method can well address the azimuth space variance of the whole scene, make the conventional frequency-domain focusing algorithms applicable to large scene focusing. Finally, the comparison results obtained by the proposed method and the reference method, validate the effectiveness of the proposed method.