基于自卷积的雷达脉冲序列盲检测

Alex Byrley, A. Fam
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引用次数: 0

摘要

本文研究了利用自卷积技术对雷达脉冲序列进行盲检测。具有恒定脉冲重复频率(PRF)的水平极化脉冲序列的自卷积与其自相关相同,只是在脉冲对称的情况下发生了时间偏移。这使得即使在恒定多普勒频移的情况下,波形也可以进行盲检测。一旦检测到,我们估计载波,解调,并估计基带序列的PRF使用对数频域匹配滤波器。我们推导了加性高斯白噪声(AWGN)的Neyman-Pearson自卷积检测阈值,并进行了数值实验来比较信噪比(SNR)与标准匹配滤波的性能。我们还举例说明了对数频率匹配滤波器的PRF估计精度。
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Blind Detection Of Radar Pulse Trains Via Self-Convolution
This paper studies the blind detection of radar pulse trains using self-convolution. The self-convolution of a horizontally polarized pulse train with a constant pulse repetition frequency (PRF) is the same as its autocorrelation, only shifted in time, provided that the pulses are symmetric. This makes the waveform amenable to blind detection even in the presence of a constant Doppler shift. Once detected, we estimate the carrier, demodulate, and estimate the PRF of the baseband train using a logarithmic frequency domain matched filter. We derive a Neyman-Pearson self-convolution detection threshold for additive white Gaussian noise (AWGN) and conduct numerical experiments to compare the Signal-to-Noise Ratio (SNR) performance against standard matched filtering. We also illustrate the logarithmic frequency matched filter’s PRF estimation accuracy.
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