同步误差条件下的空间目标双基地ISAR自聚焦算法

以空间目标为研究对象，针对双基地雷达时间、空间及频率同步误差导致的逆合成孔径雷达图像散焦问题，提出基于离散多项式相位变换的自聚焦算法。算法首先将目标平动、转动及同步误差导致的相位项统一建模为高阶多项式，利用离散多项式相位变换方法估计高阶多项式系数并据此构建补偿相位项，完成高阶相位补偿。最后进行方位压缩得到高聚焦度的二维ISAR像。算法通过选取合适的延时参数及成像积累时间可得到高精度参数估计及相位补偿，理论分析和仿真校验了算法性能优于常用的非参数化自聚焦算法。

Bistatic ISAR Autofocusing Algorithm of a Space Target in Presence of Synchronization Errors

During the bistatic inverse synthetic aperture radar imaging (ISAR) of a space target, synchronization errors of time, space and frequency can cause ISAR image defocusing. To solve this problem, an autofocusing algorithm based on discrete polynomial phase transformation is proposed. The phase term caused from the translation, rotation and synchronization errors is generally modelled as a high-order polynomial. Then, the higher order polynomial coefficients used to create the compensation phase term are estimated based on the discrete polynomial phase transformation. Based on the compensation phase term, the higher-order phase is compensated by conjugate multiplication. Finally, higher focusing-degree two-dimension ISAR image is generated. The high precision parameters estimation and phase compensation can be realized by choosing the appropriate time-delay parameter and imaging accumulation time. Theoretical analysis and simulation validate that the performance of the proposed algorithm is more effective than that of the non-parameterized algorithm.