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Calibration of Linear Time-Varying Frequency Errors for Distributed ISAR Imaging Based on the Entropy Minimization Principle

机译:基于熵最小化原理的分布式ISAR成像线性时变频率误差校准

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The inevitable frequency errors owing to the frequency mismatch of a transmitter and receiver oscillators could seriously deteriorate the imaging performance in distributed inverse synthetic aperture radar (ISAR) system. In this paper, for this issue, a novel method is proposed to calibrate the linear time-varying frequency errors (LTFE) between the transmitting node and the receiving node. The cost function is constructed based on the entropy minimization principle and the problem of LTFE calibration is transformed into cost function optimization. The frequency error coefficient, which minimizes the image entropy, is obtained by searching optimum solution in the solution space of cost function. Then, the original signal is calibrated by the frequency error coefficient. Finally, the effectiveness of the proposed method is demonstrated by simulation and real-data experiments.
机译:由于发射器和接收器振荡器的频率不匹配而不可避免的频率误差可能会严重降低分布式逆合成孔径雷达(ISAR)系统中的成像性能。 在本文中,对于该问题,提出了一种新的方法来校准发送节点和接收节点之间的线性时变频误差(LTFE)。 基于熵最小化原理构建成本函数,将LTFE校准的问题变为成本函数优化。 通过在成本函数的解决方案空间中搜索最佳解决方案来获得最小化图像熵的频率误差系数。 然后,原始信号被频率误差系数校准。 最后,通过模拟和实数据实验证明了所提出的方法的有效性。

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