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A super-resolving imaging algorithm of forward-looking SAR based on compressive sensing

机译:基于压缩感知的前视SAR超分辨成像算法

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As having the imaging ability of area in front of flight direction, forward-looking synthetic aperture radar (SAR) has become a hot topic in areas of SAR research. Nevertheless, the currently exploited imaging algorithms of forward-looking SAR suffer from poor azimuth resolution induced by limited azimuth aperture length. To address this challenge, we develop a super-resolving imaging algorithm for forward-looking SAR based on compressive sensing theory. Firstly, the spatial geometry and signal model of forward-looking SAR is analyzed. After that, the compressive sensing theory is introduced to improve azimuth resolution. Imaging simulations based on Ku-band image data from the MiniSAR system demonstrate the effectiveness of the proposed method.
机译:由于具有飞行方向前方区域的成像能力,前视合成孔径雷达(SAR)已成为SAR研究领域的热门话题。然而,当前使用的前视SAR成像算法由于有限的方位角孔径长度而导致方位角分辨率差。为了解决这一挑战,我们基于压缩感测理论为前瞻性SAR开发了超分辨成像算法。首先,对前瞻性SAR的空间几何和信号模型进行了分析。之后,引入压缩感测理论以提高方位分辨率。基于MiniSAR系统的Ku波段图像数据的成像仿真证明了该方法的有效性。

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