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ISAR Imaging Based on Bivariate Empirical Mode Decomposition and Wigner-Ville Distribution

机译:基于双变量实证分解和Wigner-Ville分布的ISAR成像

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An Inverse Synthetic Aperture Radar (ISAR) imaging method based on Bivariate Empirical Mode Decomposition (BEMD) and Wigner-Ville Distribution (WVD) is proposed in this paper. This method effectively reduces the cross-term interference and has less false frequency, leading to better quality of reconstructed image. Simulation results verify the better performance of proposed BEMD-WVD method compared with WVD method and Complex Empirical Mode Decomposition (CEMD) with WVD (CEMD-WVD) method.
机译:本文提出了一种基于双变量经验模式分解(BEMD)和Wigner-Ville分布(WVD)的逆合成孔径雷达(ISAR)成像方法。该方法有效地降低了横级干扰并且具有较少的假频率,导致更好的重建图像质量。仿真结果验证了与WVD方法和WVD(CEMD-WVD)方法的复杂经验模式分解(CEMD)相比,验证了拟议的BEMD-WVD方法的性能更好。

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