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An accumulated Error Estimation Method for Nonuniform SAR Based on Sparse Observation

机译:基于稀疏观察的非均匀SAR累计误差估计方法

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Non-uniform sampling error may cause defocusing in the reconstructed images. In the observation process, the observation positions are usually not known perfectly, and it is too expensive to estimate the position of each sample point. Here, from the error model analysis, we simplify the position error of each sampling point to an accumulated error in a synthetic aperture time. a Gaussian weighted projection coefficient sum by sparse observation matrix is used as the discrimination, and the error parameter is obtained by the golden ratio optimization algorithm with a chaotic sequences. Experimental results verify the effectiveness and efficiency of the proposed method.
机译:非均匀采样误差可能导致重建图像中的散焦。在观察过程中,观察位置通常完全不知道,估计每个采样点的位置太昂贵。这里,从错误模型分析中,我们将每个采样点的位置误差简化到合成孔径时间中的累积误差。通过稀疏观察矩阵的高斯加权投影系数和作为识别,并且误差参数通过具有混沌序列的金色比优化算法获得。实验结果验证了该方法的有效性和效率。

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