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Efficient motion compensation of SAR imagery by refocusing approach

机译:通过重焦方法高效运动补偿SAR图像

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Current motion compensation algorithms for a moving object on synthetic aperture radar (SAR) imagery by refocusing are accurate, but they suffer from a severe computational efficiency problem. If the step size of an assumed target velocity is too large, one could miss the true target velocity, whereas too small a step size would lead to a considerable computation load. To address this issue, the way motion error affects a compressed signal should be understood. In this paper, we briefly mentioned the concept of velocity correlation function (VCF) to describe the sensitivity of a SAR compressed signal to motion error, and derived its analytical model. After conducting a sensitivity study based on the model, the VCF was generalized to a velocity correlation map, which visualizes a sensitivity of the SAR system parameters to target motion in both the range and the azimuth directions simultaneously. In addition, a sensitivity study of the VCF of some real SAR sensors including ALOS-2 was also conducted.
机译:通过重焦,合成孔径雷达(SAR)图像上的移动物体的当前运动补偿算法是准确的,但它们遭受严重的计算效率问题。如果假设的目标速度的步长太大,则可能会错过真正的目标速度,而阶梯尺寸太小会导致相当大的计算负荷。为了解决这个问题,应该理解运动错误影响压缩信号的方式。在本文中,我们简要介绍了速度相关函数(VCF)的概念来描述SAR压缩信号与运动错误的灵敏度,并导出其分析模型。在基于模型进行灵敏度研究之后,VCF广泛地推广到速度相关图,其可视化SAR系统参数同时在范围和方位角方向上的目标运动的灵敏度。此外,还进行了对包括Alos-2的一些真实SAR传感器的VCF的灵敏度研究。

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