scholarly journals Inter-channel uniformity of a microwave sounder in space

2017 ◽  
Author(s):  
Martin Burgdorf ◽  
Imke Hans ◽  
Marc Prange ◽  
Theresa Lang ◽  
Stefan A. Buehler
Keyword(s):  
Radio Frequency ◽  
Local Oscillator ◽  
Radio Frequency Interference ◽  
The Moon ◽  
Deep Space ◽  
Calibration Target ◽  
Frequency Shifts ◽  
Microwave Sounding Unit ◽  
Obvious Reason ◽  
Microwave Sounding

Abstract. We analyzed intrusions of the Moon in the deep space view of the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite and found no significant discrepancies in the signals from the different sounding channels between 2001 and 2008. Earlier investigations, however, had detected biases of up to 10 K by using simultaneous nadir overpasses of NOAA-16 with other satellites. These discrepancies in the observations of Earth scenes cannot be due to non-linearity of the receiver or contamination of the deep space view without affecting the signal from the Moon as well. As major anomalies of the on-board calibration target and frequency shifts of the local oscillator were not present, either, the most obvious reason for the degrading photometric stability is radio frequency interference in combination with a strongly decreasing gain. By means of the chosen example we demonstrate the usefulness of the Moon for investigations of the performance of microwave sounders in flight.

scholarly journals Inter-channel uniformity of a microwave sounder in space

2018 ◽  
Vol 11 (7) ◽  
pp. 4005-4014 ◽  
Author(s):  
Martin Burgdorf ◽  
Imke Hans ◽  
Marc Prange ◽  
Theresa Lang ◽  
Stefan A. Buehler
Keyword(s):  
Radio Frequency ◽  
Local Oscillator ◽  
Radio Frequency Interference ◽  
The Moon ◽  
Deep Space ◽  
Calibration Target ◽  
Microwave Sounding Unit ◽  
Obvious Reason ◽  
Microwave Sounding ◽  
Advanced Microwave Sounding Unit

Abstract. We analyzed intrusions of the Moon in the deep space view of the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite and found no significant discrepancies in the signals from the different sounding channels between 2001 and 2008. However, earlier investigations had detected biases of up to 10 K, by using simultaneous nadir overpasses of NOAA-16 with other satellites. These discrepancies in the observations of Earth scenes cannot be due to non-linearity of the receiver or contamination of the deep space view without affecting the signal from the Moon as well. As neither major anomalies of the on-board calibration target nor the local oscillator were present, we consider radio frequency interference in combination with a strongly decreasing gain the most obvious reason for the degrading photometric stability. By means of the chosen example we demonstrate the usefulness of the Moon for investigations of the performance of microwave sounders in flight.

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 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.

ANALYSIS OF POTENTIAL RADIO FREQUENCY INTERFERENCE ON ANTENNA POSITIONER (3M) IN RANCABUNGUR GROUND STATION

2019 ◽  
Author(s):  
Rumadi Rumadi ◽  
◽  
Dicka Ariptian Rahayu ◽  
Nur Salma Yusuf Hasanah ◽  
Zhauhar Rainaldy Ardhana ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Interference ◽  
Ground Station

scholarly journals An Efficient Radio Frequency Interference (RFI) Recognition and Characterization Using End-to-End Transfer Learning

2020 ◽  
Vol 10 (19) ◽  
pp. 6885
Author(s):  
Sahar Ujan ◽  
Neda Navidi ◽  
Rene Jr Landry
Keyword(s):  
Feature Extraction ◽  
Radio Frequency ◽  
Transfer Learning ◽  
Communication Networks ◽  
Continuous Wave ◽  
Critical Role ◽  
Video Stream ◽  
Radio Frequency Interference ◽  
Wave Interference ◽  
Continuous Wave Interference

Radio Frequency Interference (RFI) detection and characterization play a critical role in ensuring the security of all wireless communication networks. Advances in Machine Learning (ML) have led to the deployment of many robust techniques dealing with various types of RFI. To sidestep an unavoidable complicated feature extraction step in ML, we propose an efficient Deep Learning (DL)-based methodology using transfer learning to determine both the type of received signals and their modulation type. To this end, the scalogram of the received signals is used as the input of the pretrained convolutional neural networks (CNN), followed by a fully-connected classifier. This study considers a digital video stream as the signal of interest (SoI), transmitted in a real-time satellite-to-ground communication using DVB-S2 standards. To create the RFI dataset, the SoI is combined with three well-known jammers namely, continuous-wave interference (CWI), multi- continuous-wave interference (MCWI), and chirp interference (CI). This study investigated four well-known pretrained CNN architectures, namely, AlexNet, VGG-16, GoogleNet, and ResNet-18, for the feature extraction to recognize the visual RFI patterns directly from pixel images with minimal preprocessing. Moreover, the robustness of the proposed classifiers is evaluated by the data generated at different signal to noise ratios (SNR).

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