Removal Of Radio Frequency Interference Research Articles

An RFI Mitigation Pipeline for CRAFTS Multi-beam Data Based on Signal Cross-Correlation Function and SumThreshold Algorithm

The increasing radio frequency interference (RFI) is a well-recognized problem in radio astronomy research. Pulsars and Fast Radio Bursts (FRBs) are high-priority science targets of the ongoing Commercial Radio Astronomy FAST Survey (CRAFTS). To improve the quality of RFI removal in searches of pulsars and FRBs based on CRAFTS multi-beam data, we here propose an intuitive but powerful RFI mitigation pipeline (CCF-ST). The “CCF-ST” is a spatial filter constructed by signal cross-correlation function (CCF) and Sum-Threshold (ST) algorithm. The RFI marking result is saved in a “mask” file, a binary format for RFI masks in PRESTO. Three known pulsars, PSR B0525-21, PSR B0621-04, and PSR J0943 + 2252 from CRAFTS L-band 19 beams data are used for evaluation of the performance of CCF-ST in comparison with other methods, such as PRESTO’s “rfifind”, ArPLS-ST and ArPLS-SF. The result shows that CCF-ST can reduce effective data loss rate and improves the detected signal-to-noise ratio of the pulsations by ∼26% and ∼18% respectively compared with PRESTO’s “rfifind” and ArPLS-ST. The CCF-ST also has the advantage of low computational cost, e.g., reducing the time consumption by ∼40% and memory consumption by ∼90% compared with ArPLS-SF. We expect that the new RFI mitigation and analysis toolkit (CCF-ST) demonstrated in this paper can be applied to CRAFTS and other multi-beam telescope observations to improve the data quality and efficiency of pulsar and FRB searches.

A Self-learning Neural Network Approach for Radio Frequency Interference Detection and Removal in Radio Astronomy

We present a novel neural network (NN) method for the detection and removal of radio frequency interference (RFI) from the raw digitized signal in the signal processing chain of a typical radio astronomy experiment. The main advantage of our method is that it does not require a training set. Instead, our method relies on the fact that the true signal of interest coming from astronomical sources is thermal and therefore described as a Gaussian random process, which cannot be compressed. We employ a variational encoder/decoder network to find the compressible information in the data stream that can explain the most variance with the fewest degrees of freedom. We demonstrate it on a set of toy problems and stored ring buffers from the Baryon Mapping eXperiment prototype. We find that the RFI subtraction is effective at cleaning simulated time streams: While we find that the power spectra of the RFI-cleaned time streams output by the NN suffer from extra signal consistent with additive noise, we find that it is generally around percent level across the band and sub 10% in contaminated spectral channels even when RFI power is an order of magnitude larger than the signal. We discuss the advantages and limitations of this method and possible implementation in the front end of future radio experiments.

Statistical analysis of radio frequency interference in microwave links using frequency scan measurements from multi-transmitter environments

Radio frequency interference (RFI) comprises undesirable distortions from other frequency bands overlapping the specified band of operation. RFI contributes to increased detected power and temperature of the baseband processing units, resulting in considerable discrepancies in the received measurements. RFI mitigation techniques have been proposed to tackle this problem. However, the cost of implementing most RFI removal algorithms can be highly prohibitive. Removing such unwanted signals would involve removing a portion of the desired intelligence, leading to a potential loss of valuable information. The requirement for experimental frequency scans to detect, and mitigate RFI becomes important. Field measurements were conducted across three microwave links located in urban environments. The spectrum analyzer and a 0.6-meter antenna dish were used for the frequency scans at 6–8 GHz in horizontal and vertical polarizations. The availability of the desired frequencies, which is key to frequency planning is presented. The cumulative distribution functions, histogram and probability density functions of the measured data, which are crucial to determining the impact of interference on the microwave links, are presented. The statistical characteristics of the measured data are highlighted. Overall, the RFI data would provide insights on RFI detection and mitigation, leading to a high quality of service for the benefit of mobile subscribers.

OUP accepted manuscript

In this paper, we investigate the emission properties of PSR J1727-2739, whose mean pulse profile has two main components, by analysing five single-pulse observations made using the Parkes 64-m radio telescope with a central frequency of 1369 MHz between 2014 April and October. The total observation time is about 6.1 hours which contains 16718 pulses after removal of radio frequency interference (RFI). Previous studies reveal that PSR J1727-2739 exhibits both nulling and subpulse drifting. We estimate the nulling fraction to be 66%, which is consistent with previously published results. In addition to the previously known subpulse drifting in the leading component, we also explore the drifting properties for the trailing component. We observe two distinct drift modes whose vertical drift band separations ($P_{3}$) are consistent with earlier studies. We find that both profile components share the same drift periodicity $P_{3}$ in a certain drift mode, but the measured horizontal separations ($P_{2}$) are quite different for them. That is, PSR J1727-2739 is a pulsar showing both changes of drift periodicity $P_{3}$ between different drift modes and drift rate variations between components in a given drift mode. Pulsars exhibiting nulling along with drift mode changing, such as PSR J1727-2739, give an unique opportunity to investigate the physical mechanism of these phenomena.

Applying saliency-map analysis in searches for pulsars and fast radio bursts

Context. We investigate the use of saliency-map analysis to aid in searches for transient signals, such as fast radio bursts and individual pulses from radio pulsars. Aims. Our aim is to demonstrate that saliency maps provide the means to understand predictions from machine learning algorithms and can be implemented in pipelines used to search for transient events. Methods. We implemented a new deep learning methodology to predict whether any segment of the data contains a transient event. The algorithm was trained using real and simulated data sets. We demonstrate that the algorithm is able to identify such events. The output results are visually analysed via the use of saliency maps. Results. We find that saliency maps can produce an enhanced image of any transient feature without the need for de-dispersion or removal of radio frequency interference. The maps can be used to understand which features in the image were used in making the machine learning decision and to visualise the transient event. Even though the algorithm reported here was developed to demonstrate saliency-map analysis, we have detected a single burst event, in archival data, with dispersion measure of 41 cm−3 pc that is not associated with any currently known pulsar.

Ionogram RFI Rejection Using an Autoregressive Interpolation Process

AbstractDefence Science and Technology Group's Digital Oblique Receiving System (DORS) is a direct‐digital high‐frequency ionosonde receiver, capable of collecting high‐quality ionograms simultaneously on multiple oblique ionospheric paths. One of the key signal processing steps that run on board the receiver is a novel technique for the detection and removal of radio frequency interference (RFI). In the down‐converted narrow‐band time series, external RFI sources manifest as impulsive noise, often many orders of magnitude stronger than the ionosonde signal of interest. The RFI rejection technique applies a threshold detector to the whitened data, to locate the corrupt samples, and then replaces the bad data using forward and backward linear prediction, based on an autoregressive model of the desired ionosonde signal. Algorithm performance is evaluated using a set of simple statistics and ~6,000 DORS ionograms from central Australia. Compared to a more traditional approach of clipping the strong RFI impulses, the new technique significantly reduces instances of undersuppression and recovers more of the weaker propagation mode content in the ionogram. The result is a much cleaner image for the DORS automatic feature extraction and parameterized fitting technique.

High-resolution imaging of SNR IC443 and W44 with the Sardinia Radio Telescope

AbstractWe present single-dish imaging of the well-known Supernova Remnants (SNRs) IC443 and W44 at 1.5 GHz and 7 GHz with the recently commissioned 64-m diameter Sardinia Radio Telescope (SRT). Our images were obtained through on-the-fly mapping techniques, providing antenna beam oversampling, automatic baseline subtraction and radio-frequency interference removal. It results in high-quality maps of the SNRs at 7 GHz, which are usually lacking and not easily achievable through interferometry at this frequency due to the very large SNR structures. SRT continuum maps of our targets are consistent with VLA maps carried out at lower frequencies (at 324 MHz and 1.4 GHz), providing a view of the complex filamentary morphology. New estimates of the total flux density are given within 3% and 5% error at 1.5 GHz and 7 GHz respectively, in addition to flux measurements in different regions of the SNRs.

Radio-frequency interference mitigating hyperspectral L-band radiometer

Abstract. Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal of current spaceborne L-band passive microwave radiometers. These spaceborne radiometers operate within the protected passive remote sensing and radio-astronomy frequency allocation of 1400–1427 MHz but nonetheless are still subjected to frequent RFI intrusions. We present a unique surface-based and airborne hyperspectral 385 channel, dual polarization, L-band Fourier transform, RFI-detecting radiometer designed with a frequency range from 1400 through ≈ 1550 MHz. The extended frequency range was intended to increase the likelihood of detecting adjacent RFI-free channels to increase the signal, and therefore the thermal resolution, of the radiometer instrument. The external instrument calibration uses three targets (sky, ambient, and warm), and validation from independent stability measurements shows a mean absolute error (MAE) of 1.0 K for ambient and warm targets and 1.5 K for sky. A simple but effective RFI removal method which exploits the large number of frequency channels is also described. This method separates the desired thermal emission from RFI intrusions and was evaluated with synthetic microwave spectra generated using a Monte Carlo approach and validated with surface-based and airborne experimental measurements.

Digital Terrestrial Video Broadcast Interference Suppression in Forward-Looking Ground Penetrating Radar Systems

In this paper we show how radio frequency interference (RFI) generated by digital video broadcasting terrestrial and digital audio broadcasting transmitters can be an important noise source for forward-looking ground penetrating radar (FLGPR) systems. Even in remote locations the average interference power sometimes exceeds ultra-wideband signals by many dB, becoming the limiting factor in the system sensitivity. The overall problem of RFI and its impact in GPR systems is briefly described and several signal processing approaches to removal of RFI are discussed. These include spectral estimation and coherent subtraction algorithms and various filter approaches which have been developed and applied by the research community in similar contexts. We evaluate the performance of these methods by simulating two different scenarios submitted to real RFI acquired with a FLGPR system developed at the Fraunhofer Institute for High Frequency Physics and Radar Techniques (FHR), (GER). The effectiveness of these algorithms in removing RFI is presented using some performance indices after suppression.

Detecting cosmic rays with the LOFAR radio telescope

The low frequency array (LOFAR), is the first radio telescope designed with the capability to measure radio emission from cosmic-ray induced air showers in parallel with interferometric observations. In the first $\sim 2\,\mathrm{years}$ of observing, 405 cosmic-ray events in the energy range of $10^{16} - 10^{18}\,\mathrm{eV}$ have been detected in the band from $30 - 80\,\mathrm{MHz}$. Each of these air showers is registered with up to $\sim1000$ independent antennas resulting in measurements of the radio emission with unprecedented detail. This article describes the dataset, as well as the analysis pipeline, and serves as a reference for future papers based on these data. All steps necessary to achieve a full reconstruction of the electric field at every antenna position are explained, including removal of radio frequency interference, correcting for the antenna response and identification of the pulsed signal.

The “Sausage” and “Toothbrush” clusters of galaxies and the prospects of LOFAR observations of clusters of galaxies

AbstractLOFAR, the Low Frequency Radio Array, is a new pan‐European radio telescope that is almost fully operational. One of its main drivers is to make deep images of the low frequency radio sky. To be able to do this a number of challenges need to be addressed. These include the high data rates, removal of radio frequency interference, calibration of the beams and correcting for the corrupting influence of the ionosphere. One of the key science goals is to study merger shocks, particle acceleration mechanisms and the structure of magnetic fields in nearby and distant merging clusters. Recent studies with the GMRT and WSRT radio telescopes of the “Sausage” and the “Toothbrush” clusters have given a very good demonstration of the power of radio observations to study merging clusters. Recently we discovered that both clusters contain relic and halo sources, large diffuse regions of radio emission not associated with individual galaxies. The 2 Mpc northern relic in the Sausage cluster displays highly aligned magnetic fields and and exhibits a strong spectral index gradient that is a consequence of cooling of the synchrotron emitting particles in the post‐shock region. We have argued that these observations provide strong evidence that shocks in merging clusters are capable of accelerating particles. For the Toothbrush cluster we observe a puzzling linear relic that extends over 2 Mpc. The proposed scenario is that a triplemerger can lead to such a structure. With LOFAR's sensitivity it will not only be possible to trace much weaker shocks, but also to study those shocks due to merging clusters up to redshifts of at least one. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Post-correlation filtering techniques for off-axis source and RFI removal

Techniques to improve the data quality of interferometric radio observations are considered. Fundaments of fringe frequencies in the uv-plane are discussed and filters are used to attenuate radio-frequency interference (RFI) and off-axis sources. Several new applications of filters are introduced and tested. A low-pass filter in time and frequency direction on single baseline data is successfully used to lower the noise in the area of interest and to remove sidelobes coming from unmodelled off-axis sources and RFI. Related side effects of data integration, averaging and gridding are analysed, and shown to be able to cause ghosts and an increase in noise, especially when using long baselines or interferometric elements that have a large field of view. A novel projected fringe low-pass filter is shown to be potentially useful for first order source separation. Initial tests show that the filters can be several factors faster compared to common source separation techniques such as peeling and a variant of peeling that is currently being tested on LOFAR observations called "demixed peeling". Further testing is required to support the performance of the filters.

The generalized spectral kurtosis estimator

Abstract Due to its conceptual simplicity and its proven effectiveness in real-time detection and removal of radio frequency interference (RFI) from radio astronomy data, the spectral kurtosis (SK) estimator is likely to become a standard tool of a new generation of radio telescopes. However, the SK estimator in its original form must be developed from instantaneous power spectral density estimates, and hence cannot be employed as an RFI excision tool downstream of the data pipeline in existing instruments where any time averaging is performed. In this Letter, we develop a generalized estimator with wider applicability for both instantaneous and averaged spectral data, which extends its practical use to a much larger pool of radio instruments.

Airborne radio-frequency interference studies at C-band using a digital receiver

Corruption of C-band microwave brightness observations by radio-frequency interference (RFI) has been reported in recent data from orbiting radiometers; methods for mitigating these effects are of great importance for the design of future spaceborne microwave radiometers. One approach that has been suggested involves the use of multiple subchannels at C-band as opposed to a single channel; the use of multiple subchannels allows RFI to be detected and mitigated by analyzing relationships among subchannel brightnesses. While this approach has been utilized in previous airborne measurements, demonstrations of the RFI mitigation performance achieved have been difficult to obtain. To address this issue, an enhanced airborne system for observing radio-frequency interference effects on C-band microwave radiometers was developed, and is described in this paper. The system includes a traditional microwave radiometer with four C-band subchannels, so that RFI removal is possible using a subchannel mitigation algorithm. In addition, the system includes a digital receiver with the capability of providing high temporal and spectral resolution observations of interference. This high-resolution data allows improved understanding of RFI sources to be obtained, and also allows analysis of subchannel mitigation algorithm performance. Observations using the system in a test flight near Wallops Island, VA are described. Results show the four subchannel approach generally to be effective in mitigating the observed RFI sources, although examples are also illustrated using the digital receiver data to demonstrate failure of this approach. While studies of the digital receiver data alone could be performed to demonstrate further improvements in RFI mitigation, issues with this initial dataset limit the extent of such studies. Nevertheless, the results obtained still demonstrate qualitatively the improved RFI mitigation that can be achieved in brightness observations through the use of digital receivers

An algorithm for the removal of radio frequency interference in ionospheric backscatter sounding

In common with all wideband ionospheric sounding systems the backscatter technique is susceptible to contamination by radio frequency interference. The eradication of such interference is imperative in systems required to automatically interrogate the backscatter sounder data base. This paper presents the results of the development of an algorithm designed for that purpose. The philosophy guiding the design is presented, together with the results of a computer simulation designed to simultaneously validate the proposed approach and derive an appropriate threshold. Details of the implementation are provided together with data demonstrating the effectiveness. The algorithm is capable of being implemented in any backscatter sounder system featuring an adequate digital signal processing capability.