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A SAR imaging technique for the target of complex azimuth envelope based on information extraction

机译:基于信息提取的复杂方位角包络目标的SAR成像技术

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This paper talks about an innovative method for constructing SAR image from raw data when range migration phenomenon is obvious. Here, SAR raw data works as input. A set of range migration curves (RMC) will be extracted from its range compression result. After that, parameters gained from curve fitting provide physical location and normalized backscattering coefficient of targets, and thus a SAR image is constructed. In this algorithm, Random Sample Consensus (RANSAC) offers idea about pixels classification of different point targets. Moreover, the least-squares distance gives measure to classify pixels belonging to different point targets. It is shown that range migration curve can be regarded as a parabola when estimating the parameters by curve fitting. These estimated parameters construct SAR image well when the conventional SAR image formation algorithm fails in obtaining a good one. In this paper, experimental results are conducted to illustrate the superiority of the algorithm.
机译:本文谈到了在范围迁移现象显而易见的时候从原始数据构建S​​AR图像的创新方法。这里,SAR原始数据用作输入。将从其范围压缩结果中提取一组范围迁移曲线(RMC)。之后,从曲线拟合中获得的参数提供物理位置和标准化的反向散射系数的目标,因此构造了SAR图像。在该算法中,随机示例共识(Ransac)提供了关于不同点目标的像素分类的想法。此外,最小二乘距离给出了分类属于不同点目标的像素的量度。结果表明,在通过曲线拟合估计参数时,可以将范围迁移曲线视为抛物线。当传统的SAR图像形成算法在获得良好的时,这些估计的参数构造SAR图像。在本文中,进行实验结果以说明算法的优越性。

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