RSF不准确的机载微波光子SAR原始数据处理

Jianlai Chen;Mengliang Li;Mengdao Xing;Gang Xu;Yucan Zhu;Ruoming Li;Wangzhe Li
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引用次数: 2

摘要

由于系统不稳定等原因,系统的实际距离采样频率(RSF)可能会偏离微波光子合成孔径雷达(SAR)的理想值。这种偏差可能导致成像后严重的残余距离单元偏移,甚至距离散焦,严重影响图像质量。为了解决这一问题,本文提出了一种基于不精确系统参数估计的机载微波光子SAR成像算法。首先,该算法估计并补偿距离空间变化的运动误差,以消除该运动误差对剩余RCM和距离散焦的影响。其次,基于图像的最小熵准则,我们使用优化模型来估计实际的RSF。最后,利用现有的宽波束自动聚焦方法对方位角空间变化的运动误差进行了校正。仿真数据和实测数据处理结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Processing of Airborne Microwave Photonic SAR Raw Data With Inaccurate RSF
Due to system instability and other reasons, the actual range sampling frequency (RSF) of the system may deviate from the ideal value for the microwave photonic synthetic aperture radar (SAR). This deviation may lead to severe residual range cell migration (RCM) and even range defocus after imaging, which can seriously affect the image quality. To resolve this problem, this article proposes an airborne microwave photonic SAR imaging algorithm based on inaccurate system parameter estimation. First, the algorithm estimates and compensates for the range spatial-variant motion error to eliminate the effect of this motion error on the remaining RCM and range defocus. Second, based on the minimum entropy criterion of the image, we use the optimization model to estimate the actual RSF. Finally, the existing wide-beam autofocus method is used to correct the azimuth spatial-variant motion error. The simulation data and the measured data processing results verify the effectiveness of the proposed method.
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CiteScore
4.40
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