Stable convergence of the algorithm computing the coefficients of the LMS filter suppressing RFI in radio detection of cosmic rays in the Auger Engineering Radio Array

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F21%3A00546101" target="_blank" >RIV/68378271:_____/21:00546101 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.nima.2020.164607" target="_blank" >https://doi.org/10.1016/j.nima.2020.164607</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.nima.2020.164607" target="_blank" >10.1016/j.nima.2020.164607</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Stable convergence of the algorithm computing the coefficients of the LMS filter suppressing RFI in radio detection of cosmic rays in the Auger Engineering Radio Array

Popis výsledku v původním jazyce

Radio stations of the Auger Engineering Radio Array (AERA) investigates radio signals from coherent emissions due to geomagnetic radiation and charge excess processes. The frequency band is limited to 30–80 MHz. This range is highly contaminated by human-made RFI. In order to improve the signal to noise ratio, RFI filters have to be used to suppress this contamination. The LMS filter proposed for the RFI suppression should use correct learning factor, crucial for a stability of the filter, which could be determined by eigenvalues of the auto-correlation matrix built for ADC samples. A detailed analysis of almost one million of AERA events confirms that eigenvalues of real cosmic events taken from the AERA database fully allow their use in the LMS filters, with learning factors optimal for the most efficient RFI suppression. This type of the filter can be used in other radio cosmic ray experiments e.g. the Giant Radio Array for Neutrino Detection (GRAND).

Název v anglickém jazyce

Stable convergence of the algorithm computing the coefficients of the LMS filter suppressing RFI in radio detection of cosmic rays in the Auger Engineering Radio Array

Popis výsledku anglicky

Radio stations of the Auger Engineering Radio Array (AERA) investigates radio signals from coherent emissions due to geomagnetic radiation and charge excess processes. The frequency band is limited to 30–80 MHz. This range is highly contaminated by human-made RFI. In order to improve the signal to noise ratio, RFI filters have to be used to suppress this contamination. The LMS filter proposed for the RFI suppression should use correct learning factor, crucial for a stability of the filter, which could be determined by eigenvalues of the auto-correlation matrix built for ADC samples. A detailed analysis of almost one million of AERA events confirms that eigenvalues of real cosmic events taken from the AERA database fully allow their use in the LMS filters, with learning factors optimal for the most efficient RFI suppression. This type of the filter can be used in other radio cosmic ray experiments e.g. the Giant Radio Array for Neutrino Detection (GRAND).

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10303 - Particles and field physics

Projekt

—

Návaznosti

—

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Nuclear Instruments & Methods in Physics Research Section A

ISSN

0168-9002

e-ISSN

1872-9576

Svazek periodika

985

Číslo periodika v rámci svazku

January

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

8

Strana od-do

164607

Kód UT WoS článku

000592358200001

EID výsledku v databázi Scopus

2-s2.0-85091524546