Javadi S Hamed, Sahli Hichem, Bourdoux André
Appl Opt. 2023 Jun 10;62(17):F1-F7. doi: 10.1364/AO.482527.
Inverse synthetic aperture radar (ISAR) provides a solution to increase the radar angular resolution by observing a moving target over time. The high-resolution ISAR image should undergo a segmentation step to get the target's point cloud data, which is then used for classification purposes. Existing segmentation algorithms seek an optimal threshold in an iterative manner, which adds to the complexity of ISAR and results in an increase in the processing time. In this paper, we take advantage of the distribution of the ISAR image intensity, which is based on the Rayleigh distribution, and obtain an explicit relationship for the optimal segmentation threshold. The proposed segmentation algorithm alleviates the requirement for iterative optimization and its efficiency is shown using both simulated and experimental ISAR images.
逆合成孔径雷达（ISAR）通过对移动目标进行长时间观测，为提高雷达角分辨率提供了一种解决方案。高分辨率ISAR图像应经过分割步骤以获取目标的点云数据，然后将其用于分类目的。现有的分割算法以迭代方式寻找最优阈值，这增加了ISAR的复杂度并导致处理时间增加。在本文中，我们利用基于瑞利分布的ISAR图像强度分布，得到了最优分割阈值的显式关系。所提出的分割算法减轻了迭代优化的需求，并通过模拟和实验ISAR图像展示了其效率。
