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Sparse subband fusion imaging based on parameter estimation of geometrical theory of diffraction model

机译:基于衍射模型几何理论参数估计的稀疏子带融合成像

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摘要

This study focuses on sparse subband fusion imaging. A method based on high-precision parameter estimation of geometrical theory of diffraction (GTD) model is given. Considering the incoherence problem in each subband data, a coherent processing method is adopted in the paper. Based on an all-pole model, it makes use of the phase difference of pole and scattering coefficient between each sub-band to effectively estimate the incoherent components. After coherent processing, the high and low frequency subband data can be expressed as a uniform all-pole model. The gapped-data amplitude and phase estimation algorithm is adopted to fill up the gapped band. Finally, fusion data is gained by high precision parameter estimation of GTD-all-pole model with full-band data, such as scattering center number, scattering center type and amplitude. The experimental results of simulated data with fixed-points indicate that the resolution of onedimensional (1D) range profile and 2D inverse synthetic aperture radar (ISAR) image based on this method is better than that of each sub-band. In this way, the validity of the proposed method is proved.
机译:这项研究的重点是稀疏子带融合成像。给出了一种基于几何几何理论的高精度参数估计模型的方法。考虑到每个子带数据的不一致性问题,本文采用了一种相干处理方法。它基于全极点模型,利用极点的相位差和每个子带之间的散射系数来有效地估计不相干分量。经过相干处理,高频和低频子带数据可以表示为统一的全极点模型。采用间隙数据幅度和相位估计算法填充间隙带。最后,通过对GTD-全极点模型的高精度参数估计和全波段数据,如散射中心数,散射中心类型和幅度,获得融合数据。定点模拟数据的实验结果表明,基于该方法的一维(1D)测距剖面图和二维逆合成孔径雷达(ISAR)图像的分辨率优于每个子带。这样,证明了所提方法的有效性。

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  • 来源
    《Radar, Sonar & Navigation, IET》 |2014年第4期|318-326|共9页
  • 作者

    Tian B.; Chen Z.; Xu S.;

  • 作者单位

    Science and Technology on Automatic Target Recognition Laboratory (ATR), National University of Defense Technology, Changsha, Hunan 410073, People's Republic of China|c|;

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  • 正文语种 eng
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