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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标定

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摘要

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导致的不可避免的频率误差会严重降低分布式逆合成孔径雷达(ISAR)系统的成像性能。在本文中,针对此问题,提出了一种新颖的方法来校准发送节点和接收节点之间的线性时变频率误差(LTFE)。基于熵最小化原理构造成本函数,并将LTFE校准问题转化为成本函数优化。通过在成本函数的解空间中搜索最优解,可以获得使图像熵最小的频率误差系数。然后,通过频率误差系数校准原始信号。最后,通过仿真和真实数据实验证明了该方法的有效性。

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