运动补偿是ISAR(Inverse Synthetic Aperture Radar)成像算法中的重要步骤.本文将运动补偿归结为多参数估计问题,基于设计结构化Gram矩阵的最优化理论提出了一种运动补偿方法.该方法可分为距离对准和相位补偿两部分,其中距离对准算法通过让所有距离像之间的相关性同时逼近最大值的准则实现偏移量的估计,而相位补偿算法则通过分析信号模型推导出最优矩阵从而利用最优化方法提取相位误差.实测数据处理结果表明,这两种算法都具有较强的鲁棒性和较高的估计精度,是一种有效的运动补偿方法.
Motion compensation is a key procedure in ISAR (Inverse Synthetic Aperture Radar ) imaging. The motion com- pensation can be viewed as a multi-parameter estimation problem. Based on the designing structured Gram matrices optimization, a motion compensation method is put forward. This method consists of two parts: the range alignment algorithm and the phase com- pensation algorithm. The former estimates the offset of each range profile based on a criterion, which makes correlations among all range profiles approaching to maximum values simultaneously. And the latter can extract phase errors by means of the optimization method, in which the optimal matrix is derived from analysis on the signal model. The measured data processing result shows that the motion compensation method has strong robustness and high estimation accuracy.