太赫兹CSAR运动目标参数估计与重聚焦方法

Terahertz CSAR ground moving target parameter estimation and refocusing algorithm

摘要:

为了提高太赫兹圆周模式下的动目标运动参数估计精确度和成像质量，提出了一种太赫兹圆周合成孔径雷达(CSAR)运动目标参数估计与重聚焦方法。首先对传统的谱峰测量法进行改进，并结合动目标阴影位置来估计方位速度。与现有方法相比，该方法结合了目标的真实位置对多普勒频移的影响，提高了运动目标方位速度估计值的准确性。利用分数阶傅里叶变换(FrFt)估计方位相位的多普勒调频率，结合方位速度可得到目标距离速度的估计值。利用估计结果构造一阶和二阶相位补偿函数进行方位相位的补偿，对于残余的二次及高次相位误差，利用相位梯度自聚焦算法(PGA)进行补偿。仿真和实测数据中动目标运动参数得到了精确估计，并实现了良好聚焦，证明了所提方法的有效性，大大提高了运动目标的成像质量。

Abstract:

In order to improve the accuracy of motion parameter estimation and imaging quality of moving targets in terahertz Circular Synthetic Aperture Radar(CSAR) mode, a terahertz CSAR ground moving target parameter estimation and refocusing method is proposed. Firstly, the traditional spectral peak measurement method is improved to estimate the azimuth velocity by combining the shadow position of the moving target. Compared with the existing methods, the proposed method takes into account the influence of the real position of the target on the Doppler frequency shift, and improves the accuracy of the moving target's azimuth velocity estimation. Then the Fractional Fourier Transform(FrFt) is employed to estimate the Doppler modulation frequency of the azimuth phase, and the range velocity of the target can be estimated together with the azimuth velocity. Finally, the first-order and second-order phase compensation functions are constructed for azimuth compensation based on the estimation results, and the Phase Gradient Autofocus(PGA) algorithm is utilized to compensate for the residual quadratic and higher phase errors. The moving target motion parameters in the simulated and real CSAR data are accurately estimated and good focusing is achieved, which proves the effectiveness of the proposed method and greatly improves the imaging quality of the moving target.