This paper proposes a fast inverse synthetic aperture radar (ISAR) motion compensation (MOCOM) method. The various motion compensation methods using minimum entropy algorithm such as stage-by-stage approaching (SSA) algorithm were reported recently. However, the computational efficiency and the clearance of the ISAR image were hard to achieve simultaneously. In particular, as the number of the local minima in the entropy curve increases, the processing time takes longer to find the global minimum. In this paper, we propose a new MOCOM algorithm based on an improved SSA algorithm to reduce the processing time. The proposed algorithm uses the envelope value as the fitness function instead of the entropy value, so the number of the local minima in the entropy curve is reduced. Therefore, the entropy curve becomes simple and the required number of the phase error samples is reduced. In the simulation, the processing time is improved by 88.8% than the conventional SSA algorithm. Also, in the experiment, the processing time is improved by 87.9% ∼ 89.2%.

本文提出了一种快速逆合成孔径雷达（ISAR）运动补偿（MOCOM）方法。最近报道了使用最小熵算法的各种运动补偿方法，例如逐级逼近（SSA）算法。然而，计算效率和ISAR图像的清除很难同时实现。特别是，随着熵曲线中局部最小值的数量增加，找到全局最小值的处理时间会更长。在本文中，我们提出了一种基于改进 SSA 算法的新 MOCOM 算法，以减少处理时间。该算法使用包络值代替熵值作为适应度函数，减少了熵曲线中局部极小值的数量。所以，熵曲线变得简单，减少了所需的相位误差样本数。在仿真中，处理时间比传统的 SSA 算法提高了 88.8%。此外，在实验中，处理时间提高了 87.9% ∼ 89.2%。