An interference detection strategy for Apertif based on AOFlagger 3

Autor: A. R. Offringa, B. Adebahr, A. Kutkin, E. A. K. Adams, T. A. Oosterloo, J. M. van der Hulst, H. Dénes, C. G. Bassa, D. L. Lucero, W. J. G. Blok, K. M. Hess, J. van Leeuwen, G. M. Loose, Y. Maan, L. C. Oostrum, E. Orrú, D. Vohl, J. Ziemke
Přispěvatelé: Ministerio de Ciencia e Innovación (España), European Commission, European Research Council, German Research Foundation
Rok vydání: 2023
Předmět:
DOI: 10.48550/arxiv.2301.01562
Popis: This is an Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Context. Apertif is a multi-beam receiver system for the Westerbork Synthesis Radio Telescope that operates at 1.1–1.5 GHz, which overlaps with various radio services, resulting in contamination of astronomical signals with radio-frequency interference (RFI). Aims. We analyse approaches to mitigate Apertif interference and design an automated detection procedure for its imaging mode. Using this approach, we present long-term RFI detection results of over 300 Apertif observations. Methods. Our approach is based on the AOFlagger detection approach. We introduce several new features, including ways to deal with ranges of invalid data (e.g. caused by shadowing) in both the SumThreshold and scale-invariant rank operator steps; pre-calibration bandpass calibration; auto-correlation flagging; and HI flagging avoidance. These methods have been implemented in a new framework that uses the Lua language for scripting, which is new in AOFlagger version 3. Results. Our approach removes RFI fully automatically, and it is robust and effective enough for further calibration and (continuum) imaging of these data. The analysis of 304 observations shows an average of 11.1% of lost data due to RFI with a large spread. We observe 14.6% RFI in auto-correlations. Computationally, AOFlagger achieves a throughput of 370 MB/s on a single computing node. Compared to published machine learning results, the method is one to two orders of magnitude faster. © The Authors 2023.
This work makes use of data from the Apertif system installed at the Westerbork Synthesis Radio Telescope owned by ASTRON. ASTRON, the Netherlands Institute for Radio Astronomy, is an institute of the Dutch Research Council (de Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO). B.A. acknowledges funding from the German Science Foundation DFG, within the Collaborative Research Center SFB1491 “Cosmic Interacting Matters – From Source to Signal”. E.A.K.A. is supported by the WISE research programme, which is financed by NWO. J.M.vd.H. and K.M.H., acknowledge funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement No. 291531 (‘HIStoryNU’). Jv.L., Y.M. and L.C.O. acknowledge funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement No. 617199 (‘ALERT’; PI: JvL). K.M.H. further acknowledges financial support from the State Agency for Research of the Spanish Ministry of Science, Innovation and Universities through the “Center of Excellence Severo Ochoa” awarded to the Instituto de Astrofísica de Andalucía (SEV-2017-0709) from the coordination of the participation in SKA-SPAIN, funded by the Ministry of Science and innovation (MICIN) and grant RTI2018-096228-B-C31 (MCIU/AEI/FEDER,UE). Jv.L. further acknowledges funding from Vici research programme ‘ARGO’ with project number 639.043.815, financed by NWO. D.V. acknowledges support from the Netherlands eScience Center (NLeSC) under grant ASDI.15.406.
With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).
Databáze: OpenAIRE
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