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

G. Nita, A. Keimpema, Z. Paragi
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引用次数: 1

Abstract

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.
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低位采样时域信号中暂态信号的统计检测与分类
本文研究了广义谱峰度(SK)估计在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工极短持续时间瞬态的性能。我们证明,在对2位时域电压执行32位FFT操作后,这两种类型的瞬态在谱域中变得彼此可区分。因此,我们证明了谱峰度估计器在VLBI数据流中自动检测感兴趣的明亮天文瞬态信号(如脉冲星或快速射电暴(FRB))的能力,这些数据流已被不必要的射频干扰严重污染。
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