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Adaptive pulse edge detection algorithm based on short-time Fourier transforms and difference of box filter

机译:基于短时傅里叶变换的自适应脉冲边缘检测算法及箱滤波器的差异

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摘要

Precise radar pulse detection is of great significance for estimating parameters in electronic countermeasure and reconnaissance. An adaptive detection algorithm is proposed, which considers short-time Fourier transforms (STFT), constant false alarm rate (CFAR) in frequency domain, and difference of box (DOB) filter. First, STFT with the Gaussian window is used to acquire the time-frequency spectrum of the radar pulse signal. Second, in order to determine the existence of the pulse, CFAR detector is introduced into the frequency domain to generate an adaptive threshold, and then the rough pulse edges are obtained by mn method. Finally, the data where the rough pulse edges locate are processed by the refined STFT and DOB filter to get the precise pulse edges. The proposed algorithm is processed in the time-frequency domain, which cannot only adapt to low signal-to-noise ratio, but also has a high measurement accuracy. We also draw parallels to the conventional energy-based detection method, the results validate that the proposed algorithm is more robust and effective in practice. Simulations via various noisy input pulse data demonstrate the viability and validity of our proposed algorithm. The algorithm has been implemented in a spaceborne radar receiver. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)
机译:精确的雷达脉冲检测对于估计电子对策和侦察的参数具有重要意义。提出了一种自适应检测算法,其考虑频域的短时傅里叶变换(STFT),常数误报率(CFAR),以及框(DOB)滤波器的差异。首先,使用具有高斯窗口的STFT来获取雷达脉冲信号的时频谱。其次,为了确定脉冲的存在,CFAR检测器被引入到频域中以产生自适应阈值,然后通过Mn方法获得粗略脉冲边缘。最后,通过精炼的STFT和DOB滤波器处理粗脉冲边缘定位的数据以获得精确的脉冲边缘。所提出的算法在时频域中处理,其不能仅适应低信噪比,而且还具有高测量精度。我们还将Parallels绘制到传统的基于能量的检测方法,结果验证了所提出的算法在实践中更具稳健和有效。通过各种噪声输入脉冲数据模拟展示了我们所提出的算法的可行性和有效性。该算法已经在空间罗达接收器中实现。 (c)2019年光学仪表工程师协会(SPIE)

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