Statistical detection and classification of transient signals in low-bit sampling time-domain signals
Document Type
Conference Proceeding
Publication Date
7-2-2018
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.
Identifier
85063073543 (Scopus)
ISBN
[9781728112954]
Publication Title
2018 IEEE Global Conference on Signal and Information Processing Globalsip 2018 Proceedings
External Full Text Location
https://doi.org/10.1109/GlobalSIP.2018.8646395
First Page
1104
Last Page
1108
Recommended Citation
Nita, Gelu M.; Keimpema, Aard; and Paragi, Zsolt, "Statistical detection and classification of transient signals in low-bit sampling time-domain signals" (2018). Faculty Publications. 8524.
https://digitalcommons.njit.edu/fac_pubs/8524
