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Millisecond Cadence Radio Frequency Interference Filters
by
Kania, Joseph W
, Lorimer, Duncan R
, Bandura, Kevin
, Prestage, Richard
in
Astrophysics
/ Human resources
/ Noise levels
/ Pulsars
/ Radio bursts
/ Radio frequency
/ Radio frequency interference
/ Radio observation
/ Radio signals
/ Radio telescopes
/ Random noise
/ Searching
/ Transients (astronomy)
2022
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Millisecond Cadence Radio Frequency Interference Filters
by
Kania, Joseph W
, Lorimer, Duncan R
, Bandura, Kevin
, Prestage, Richard
in
Astrophysics
/ Human resources
/ Noise levels
/ Pulsars
/ Radio bursts
/ Radio frequency
/ Radio frequency interference
/ Radio observation
/ Radio signals
/ Radio telescopes
/ Random noise
/ Searching
/ Transients (astronomy)
2022
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Millisecond Cadence Radio Frequency Interference Filters
by
Kania, Joseph W
, Lorimer, Duncan R
, Bandura, Kevin
, Prestage, Richard
in
Astrophysics
/ Human resources
/ Noise levels
/ Pulsars
/ Radio bursts
/ Radio frequency
/ Radio frequency interference
/ Radio observation
/ Radio signals
/ Radio telescopes
/ Random noise
/ Searching
/ Transients (astronomy)
2022
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Paper
Millisecond Cadence Radio Frequency Interference Filters
2022
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Overview
Radio Frequency Interference (RFI) greatly reduces sensitivity of radio observations to astrophysical signals and creates false positive candidates in searches for radio transients. Real signals are missed while considerable computational and human resources are needed to remove RFI candidates. In the context of transient astrophysics, this makes effective RFI removal vital to effective searches for fast radio bursts and pulsars. Radio telescopes typically sample at rates that are high enough for there to be tens to hundreds of samples along the transient's pulse. Mitigation techniques should excise RFI on this timescale to account for a changing radio frequency environment. We evaluate the effectiveness of three filters, as well as a composite of the three, that excises RFI at the cadence that the data are recorded. Each of these filters operates in a different domain and thus excises as a different RFI morphology. We analyze the performance of these four filters in three different situations: (I) synthetic pulses in Gaussian noise; (II) synthetic pulses injected into real data; (III) four pulsar observations. From these tests, we gain insight into how the filters affect both the pulse and the noise level. This allows use to outline which and how the filters should be used based on the RFI present and the characteristics of the source signal. We show by flagging a small percentage of the spectrum we can substantially improve the quality of transit observations.
Publisher
Cornell University Library, arXiv.org
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