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STATISTICAL DETECTION AND CLASSIFICATION OF TRANSIENT SIGNALS IN LOW-BIT SAMPLING TIME-DOMAIN SIGNALS

机译:低位采样时域信号中瞬态信号的统计检测和分类

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We investigate the performance of the generalized Spectral Kurtosis (SK) estimator in detecting and discriminating natural and artificial very short duration transients in the 2-bit sampling time domain Very-Long-Baseline Interferometry (VLBI) data. We demonstrate that, after a 32-bit FFT operation is performed on the 2-bit time domain voltages, these two types of transients become distinguishable from each other in the spectral domain. Thus, we demonstrate the ability of the Spectral Kurtosis estimator to automatically detect bright astronomical transient signals of interests - such as pulsar or fast radio bursts (FRB) - in VLBI data streams that have been severely contaminated by unwanted radio frequency interference.
机译:我们调查广义谱峰度(SK)估计器在2位采样时域甚长基线干涉测量(VLBI)数据中检测和区分自然和人为的非常短持续时间瞬变的性能。我们证明,在2位时域电压上执行32位FFT操作后,这两种类型的瞬变在频谱域中变得彼此可区分。因此,我们证明了光谱峰度估计器能够自动检测到被有害无线电频率干扰严重污染的VLBI数据流中感兴趣的明亮天文瞬态信号,例如脉冲星或快速无线电脉冲串(FRB)。

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