Low-frequency technology for a lunar interferometer

2020 ◽  
Vol 379 (2188) ◽  
pp. 20190575 ◽  
Author(s):  
Kristian Zarb Adami ◽  
I. O. Farhat
Keyword(s):  
Radio Frequency ◽  
Signal Detection ◽  
Radio Astronomy ◽  
Lunar Surface ◽  
Low Frequency ◽  
Radio Interferometer ◽  
Radio Frequency Interference ◽  
The Moon ◽  
Single Antenna ◽  
Global Signal

This work sketches a possible design architecture of a low-frequency radio interferometer located on the lunar surface. The design has evolved from single antenna experiments aimed at the global signal detection of the epoch of reionization (EoR) to the square kilometre array (SKA) which, when complete, will be capable of imaging the highly red-shifted H 1 -signal from the cosmic dawn through to the EoR. However, due to the opacity of the ionosphere below 10 MHz and the anthropogenic radio-frequency interference, these terrestrial facilities are incapable of detecting pre-ionization signals and the moon becomes an attractive location to build a low-frequency radio interferometer capable of detecting such cosmological signals. Even though there are enormous engineering challenges to overcome, having this scientific facility on the lunar surface also opens up several new exciting possibilities for low-frequency radio astronomy. This article is part of a discussion meeting issue ‘Astronomy from the Moon: the next decades’.

scholarly journals Protecting Space-Based Radio Astronomy

2001 ◽  
Vol 196 ◽  
pp. 324-334 ◽  
Author(s):  
V. Altunin
Keyword(s):  
Radio Frequency ◽  
Radio Astronomy ◽  
Low Frequency ◽  
Radio Frequency Interference ◽  
Lagrangian Point ◽  
Radio Telescopes ◽  
The Moon ◽  
Microwave Background ◽  
Distant Future ◽  
First Results

This paper outlines some of the radio frequency interference issues related to radio astronomy performed with space-based radio telescopes. Radio frequency interference that threatens radio astronomy observations from the surface of Earth will also degrade observations with space-based radio telescopes. However, any resulting interference could be different than for ground-based telescopes due to several factors. Space radio astronomy observations significantly enhance studies in different areas of astronomy. Several space radio astronomy experiments for studies in low-frequency radio astronomy, space VLBI, the cosmic microwave background and the submillimetre wavelengths have flown already. The first results from these missions have provided significant breakthroughs in our understanding of the nature of celestial radio radiation. Radio astronomers plan to deploy more radio telescopes in Earth orbit, in the vicinity of the L2 Sun-Earth Lagrangian point, and, in the more distant future, in the shielded zone of the Moon.

scholarly journals A survey of spatially and temporally resolved radio frequency interference in the FM band at the Murchison Radio-astronomy Observatory

2020 ◽  
Vol 37 ◽  
Author(s):  
S. J. Tingay ◽  
M. Sokolowski ◽  
R. Wayth ◽  
D. Ung
Keyword(s):  
Radio Frequency ◽  
Radio Astronomy ◽  
Angular Resolution ◽  
Low Frequency ◽  
Earth Orbit ◽  
Radio Frequency Interference ◽  
Astronomy Observatory ◽  
Frequency Range ◽  
Radio Astronomy Observatory ◽  
Imaging Mode

Abstract We present the first survey of radio frequency interference (RFI) at the future site of the low frequency Square Kilometre Array (SKA), the Murchison Radio-astronomy Observatory (MRO), that both temporally and spatially resolves the RFI. The survey is conducted in a 1 MHz frequency range within the FM band, designed to encompass the closest and strongest FM transmitters to the MRO (located in Geraldton, approximately 300 km distant). Conducted over approximately three days using the second iteration of the Engineering Development Array in an all-sky imaging mode, we find a range of RFI signals. We are able to categorise the signals into: those received directly from the transmitters, from their horizon locations; reflections from aircraft (occupying approximately 13% of the observation duration); reflections from objects in Earth orbit; and reflections from meteor ionisation trails. In total, we analyse 33 994 images at 7.92 s time resolution in both polarisations with angular resolution of approximately 3.5 $^{\circ}$ , detecting approximately forty thousand RFI events. This detailed breakdown of RFI in the MRO environment will enable future detailed analyses of the likely impacts of RFI on key science at low radio frequencies with the SKA.

scholarly journals SETI from the Moon: Avoiding Radio Pollution for Future Radio-Astronomy

1998 ◽  
Vol 11 (2) ◽  
pp. 996-999 ◽  
Author(s):  
J. Heidmann
Keyword(s):  
Radio Frequency ◽  
Radio Astronomy ◽  
High Sensitivity ◽  
Radio Frequency Interference ◽  
The Moon ◽  
Lunar Farside

AbstractBecause of the ever increasing human-made radio frequency interference (RFI), we propose to IAU a Resolution for protecting the well singled out lunar farside 100 km diameter SAHA crater from any future RFI for the scientific benefit of the coming decades high-sensitivity radioastronomy at large. Immediate and pragmatic action is strongly recommended. Our strategy, different from the ones of a recent ITU Recommendation, could increase our bargaining possibilities.

scholarly journals A New Restoration Method for Radio Frequency Interference Effects on AMSR-2 over North America

2019 ◽  
Vol 11 (24) ◽  
pp. 2917 ◽  
Author(s):  
Wangbin Shen ◽  
Zhengkun Qin ◽  
Zhaohui Lin
Keyword(s):  
Radio Frequency ◽  
Land Surface ◽  
Interpolation Method ◽  
Low Frequency ◽  
Principal Component ◽  
New Method ◽  
Radio Frequency Interference ◽  
Data Restoration ◽  
Order Of Magnitude ◽  
Restoration Method

Observations from spaceborne microwave imagers are important sources of land surface information. However, the low-frequency channels of microwave imagers are easily interfered with by active radio signals with similar frequencies. Radio frequency interference (RFI) signals are widely distributed because of the lack of frequency protection, which seriously hinders the application of microwave imager data in data assimilation and retrieval research. In this paper, a new data restoration method is proposed based on principal component analysis (PCA). Both the ideal and real reconstruction experiments show that the new method can effectively repair abnormal observations interfered by RFI compared with the commonly used Cressman interpolation method because observation information over the whole selected domain is used for restoration in the new method, whereas Cressman interpolation uses only a selection of data around the target observation. The observation errors in the data with RFI can be reduced by one order of magnitude by means of the new method and little artificial information is introduced. One-week restoration validation also proves that the new method has a stable accuracy and broad application prospects.

scholarly journals Deep learning improves identification of Radio Frequency Interference

2020 ◽  
Vol 499 (1) ◽  
pp. 379-390
Author(s):  
Alireza Vafaei Sadr ◽  
Bruce A Bassett ◽  
Nadeem Oozeer ◽  
Yabebal Fantaye ◽  
Chris Finlay
Keyword(s):  
Deep Learning ◽  
Radio Frequency ◽  
Transfer Learning ◽  
Radio Astronomy ◽  
Real Data ◽  
Radio Frequency Interference ◽  
Time Frequency ◽  
Amplitude Data ◽  
Important Challenge ◽  
Telescope Arrays

ABSTRACT Flagging of Radio Frequency Interference (RFI) in time–frequency visibility data is an increasingly important challenge in radio astronomy. We present R-Net, a deep convolutional ResNet architecture that significantly outperforms existing algorithms – including the default MeerKAT RFI flagger, and deep U-Net architectures – across all metrics including AUC, F1-score, and MCC. We demonstrate the robustness of this improvement on both single dish and interferometric simulations and, using transfer learning, on real data. Our R-Net model’s precision is approximately $90{{\ \rm per\ cent}}$ better than the current MeerKAT flagger at $80{{\ \rm per\ cent}}$ recall and has a 35 per cent higher F1-score with no additional performance cost. We further highlight the effectiveness of transfer learning from a model initially trained on simulated MeerKAT data and fine-tuned on real, human-flagged, KAT-7 data. Despite the wide differences in the nature of the two telescope arrays, the model achieves an AUC of 0.91, while the best model without transfer learning only reaches an AUC of 0.67. We consider the use of phase information in our models but find that without calibration the phase adds almost no extra information relative to amplitude data only. Our results strongly suggest that deep learning on simulations, boosted by transfer learning on real data, will likely play a key role in the future of RFI flagging of radio astronomy data.

Optimizing Processing Time of Radio-Astronomy Antenna Simulations Using FEKO

2020 ◽  
Vol 35 (10) ◽  
pp. 1153-1160
Author(s):  
Rowanne Steiner ◽  
Daniel Ung ◽  
Anouk Hubrechsen ◽  
Robert Jones ◽  
Randall Wayth ◽  
...  
Keyword(s):  
Radio Astronomy ◽  
Low Frequency ◽  
Computation Time ◽  
Field Pattern ◽  
Mean Deviation ◽  
Antenna Element ◽  
Single Antenna ◽  
Operational Frequency ◽  
Square Kilometer Array ◽  
Far Field Pattern

The far-field pattern of a geometrically large and complex antenna used in low-frequency radio astronomy is computationally expensive to simulate on electromagnetic simulators, such as FEKO. For example, one station of the Square Kilometer Array, which consists of 256 log-periodic antenna elements, will take years to simulate using the full CAD model for the full operational frequency band. This paper focuses on reducing the simulation time for a single antenna element by simplifying the simulation model, thus decreasing the number of unknowns that have to be solved in a simulation. An iterative process for optimizing the simplification of such an element is described, while keeping the reflection coefficient within 1 dB absolute mean deviation of the measured data. After four iterations, the amount of unknowns to be solved, which includes the number of triangles and segments, was reduced from 29,307 to 11,991. This decreased the computation time by 86.5%, making array simulations feasible. Using the techniques described in the paper, other antenna constructions can benefit from it and be simulated more efficiently.

Implementing RFI Mitigation in Radio Science

2019 ◽  
Vol 08 (01) ◽  
pp. 1940010 ◽  
Author(s):  
Willem A. Baan
Keyword(s):  
Radio Frequency ◽  
Data Acquisition ◽  
Radio Astronomy ◽  
Data Acquisition System ◽  
Detection Methods ◽  
Radio Frequency Interference ◽  
Post Processing ◽  
Science Data ◽  
Radio Science ◽  
Mitigation Methods

This paper presents an overview of methods for mitigating radio frequency interference (RFI) in radio science data. The primary purpose of mitigation is to assist observatories to take useful data outside frequency bands allocated to the Science Services (Radio Astronomy Service (RAS) and Earth Exploration Service (EESS)): mitigation should not be needed within passive bands. Mitigation methods may be introduced at a variety of points within the data acquisition system in order to lessen the RFI intensity and to limit the damage it causes. These methods range from proactive methods to changing the local RFI environment by means of regulatory manners, to pre- and post-detection methods, to various pre-processing methods, and to methods applied at or post-processing.

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