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Synthetic generation of SAR raw data for complex scenes

机译:综合生成复杂场景的SAR原始数据

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Abstract: In this paper, a much more rapid method of raw data generation is applied, starting by simulating the SAR image itself. Conventional methods of translating a thermal IR- or photographic image into a SAR image are first briefly reviewed. The complex numbers representing the SAR image are then converted to radar raw data using the SAR-processing algorithms backwards. The key transform is the scene center focusing, which ties together SAR data and sensor geometry. This method of generating raw data is shown to be several orders of magnitude faster than the direct method described above, and raw data from the I- and Q-channels can readily be simulated even on a PC. The effects of internal noise and phase errors, due to imperfect motion compensation, can also be included and simulated in detail. The method is exemplified, showing the phase error effect on the SAR-image of an urban scene, the use of autofocusing to restore the image resolution, and finally the degradation due to additive noise on the collected SAR raw data.!3
机译:摘要:在本文中,从模拟SAR图像本身开始,应用了一种更为快速的原始数据生成方法。首先简要回顾一下将热红外或摄影图像转换成SAR图像的常规方法。然后使用SAR处理算法将代表SAR图像的复数转换为雷达原始数据。关键的变换是场景中心聚焦,它将SAR数据和传感器几何形状联系在一起。这种生成原始数据的方法显示出比上述直接方法快几个数量级,并且即使在PC上,也可以轻松地模拟来自I通道和Q通道的原始数据。由于不完善的运动补偿,内部噪声和相位误差的影响也可以包括在内并进行详细模拟。举例说明了该方法,显示了相位误差对城市场景SAR图像的影响,使用自动聚焦以恢复图像分辨率以及最终由于累加噪声而对所收集的SAR原始数据造成的劣化!3

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