一种低信噪比下稳健的ISAR平动补偿方法

远距离小目标/隐身目标逆合成孔径雷达成像在目标检测系统中具有重要作用，然而由于回波信号存在信噪比（Signal-to-Noise Ratio，SNR）低等问题，使得传统基于距离包络对齐的平动补偿方法失效；导致后续初相校正和方位聚焦处理性能急剧下降.针对该问题，本文提出一种低信噪比下参数化平动补偿方法.首先，将回波信号建模为多成分的多项式相位信号，并通过挖掘运动目标上所有散射体具有相同的平动历程这一先验信息，利用相位差分（Phase Differencing，PD）和Keystone变换将目标上所有散射体能量聚集到同一距离单元.然后，通过相干积累三次相位函数将该距离单元内的所有散射体能量集中到一个强点，进而估计出目标平动参数实现低SNR下平动补偿.最后，理论分析和实测数据实验验证了该方法的有效性.

A Robust Translational Motion Compensation Method for ISAR Imaging Under Low SNR Environment

Inverse synthetic aperture radar (ISAR) imaging for long range small/stealthy target plays an important role in the field of national defense surveillance.However,the performances of the traditional envelop-based range alignment method dramatically degrade due to low signal-to-noise ratio (SNR) of received echo signal,which leads to the inapplicability for the subsequent phase adjustment or azimuth focus.In this paper,a parametric-based approach is proposed to perform joint range alignment and phase adjustment.To that end,translational motion is modeled as multi-component polynomial phase signal (PPS),and inspired by the fact that all the scatterers in the moving target experience the same translational range history,the phase difference (PD) operation and Keystone transform (KT) are utilized to transform the energy of all the scatterers into one range cell.Second,a coherently integrated cubic phase function (CICPF) is developed to focus the energy of all the scatterers onto a peak point,from which the polynomial coefficients can be obtained accurately to realize the translational motion compensation in low SNR environment.Finally,theoretical analysis and experimental results are also provided to validate the effectiveness of the proposed method.