中文摘要：

在复杂运动目标的逆合成孔径雷达成像中，由于转动矢量的时变会产生方位向的高阶相位项，导致方位成像的严重散焦，传统的距离-多普勒算法和线性调频模型已不再适用．因此，在建立逆合成孔径雷达成像回波信号为立方相位信号形式的基础上，提出了利用高阶模糊函数-吕氏分布特性的逆合成孔径雷达成像算法．首先，根据高阶模糊函数和吕氏分布思想定义了双延时参数化瞬时自相关函数，并利用变尺度操作去除耦合及快速傅里叶变换实现信号能量积累．然后，利用得到的高阶模糊函数-吕氏分布完成运动参数的非搜索估计和目标逆合成孔径雷达成像．由于引入可调整的缩放因子，该算法能够在保证成像质量和运算效率的基础上，有效避免谱模糊，灵活应对更加多变和恶劣的成像环境．仿真结果验证了该算法的有效性．

英文摘要：

In ISAR imaging for targets with the complex motion, since the azimuth high order phase terms caused by the time-varying rotation vector will deteriorate the azimuth focusing quality, the traditional RD algorithm and LFM model are not appropriate. Thereby, in the case when the received signal can be modeled as cubic phase signals （CPSs）, this paper proposes an ISAR imaging algorithm based on HAF- LVD （high-order ambiguity function-Lv＇s distribution）. First, this algorithm defines a novel double lag parametric instantaneous autocorrelation function, and then applies the scaling operator to remove the coupling and utilizes FFT to achieve the energy accumulation. Finally, the non-searching estimation of the moving parameter and the ISAR images for targets are accomplished by the obtained HAF-LVD. Because of the introduction of the scaling factor, this algorithm can flexibly deal with more changeful and hostile ISAR environment without loss of the anti-noise performance and computational efficiency. Simulation results validate the effectiveness of the ISAR imaging approach.