基于子图像变标的非线性轨迹SAR成像及其自聚焦方法

Nonlinear Trajectory Synthetic Aperture Radar Imaging and Autofocus Algorithm Based on Sub-image Nonlinear Chirp Scaling

合成孔径雷达(SAR)的非线性轨迹运动可能会在雷达回波信号中引入严重的二维空变特性,因此基于方位平移不变性假设的传统频域成像算法不再适用于非线性轨迹SAR的高精度成像。现有非线性轨迹SAR成像算法通常采用复杂的非线性变标(NCS)校正回波信号的方位空变特性,然而NCS参数过多导致算法复杂,使得其当存在较大平台运动测量误差时无法与现有自聚焦算法有效结合。针对该问题,该文提出一种基于子图像NCS的非线性轨迹SAR成像及其自聚焦方法,在保证成像精度的前提下能够减少NCS的参数数量,更有利于后续的自聚焦处理。仿真与实测数据处理验证了所提方法的有效性。

The radar echo signal may experience substantial two-dimensional spatial variance due to the nonlinear Synthetic Aperture Radar(SAR)trajectory.The traditional frequency-domain imaging algorithms based on the assumption of azimuth translational invariance are unsuitable for high-precision imaging of nonlinear trajectory SAR.Therefore,for nonlinear trajectory SAR imaging,the azimuth spatial variance of the echo signals is typically rectified using complex Nonlinear Chirp Scaling(NCS).However,when there are substantial motion errors,it cannot be effectively combined with the current autofocus algorithms considering the complexity of the algorithm due to too many NCS parameters.Thus,to address this issue,this study proposes a nonlinear trajectory SAR imaging and autofocus method according to the sub-image NCS,which can reduce the number of NCS parameters and ensure imaging accuracy;moreover,it is more conducive to the subsequent autofocus processing.The effectiveness of the suggested approach is confirmed by simulation and measured data processing.