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

Hui Sheng, Bingqi Zhu, Yesheng Gao, Kaizhi Wang, Xingzhao Liu, Yiran Jin
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Abstract

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.
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基于信息提取的复杂方位包络目标SAR成像技术
本文讨论了在距离偏移现象明显的情况下,利用原始数据构造SAR图像的一种创新方法。这里,SAR原始数据作为输入。从距离压缩结果中提取一组距离偏移曲线(RMC)。然后,由曲线拟合得到的参数提供目标的物理位置和归一化后向散射系数,从而构建SAR图像。在该算法中,随机样本一致性(RANSAC)为不同点目标的像素分类提供了思路。此外,最小二乘距离给出了对属于不同点目标的像素进行分类的度量。结果表明,在拟合参数时,距离偏移曲线可以看作抛物线。在常规SAR成象算法无法得到好的SAR图像的情况下,这些估计参数可以很好地构建SAR图像。本文通过实验结果说明了该算法的优越性。
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