Radio Frequency Interference Mitigation Techniques Research Articles

Low Complexity Radio Frequency Interference Mitigation for Radio Astronomy Using Large Antenna Array

With the ongoing growth in radio communications, there is an increased contamination of radio astronomical source data, which hinders the study of celestial radio sources. In many cases, fast mitigation of strong radio frequency interference (RFI) is valuable for studying short lived radio transients so that the astronomers can perform detailed observations of celestial radio sources. The standard method to manually excise contaminated blocks in time and frequency makes the removed data useless for radio astronomy analyses. This motivates the need for better RFI mitigation techniques for array of size M antennas. Although many solutions for mitigating strong RFI improves the quality of the final celestial source signal, many standard approaches require all the eigenvalues of the spatial covariance matrix ([Formula: see text]) of the received signal, which has [Formula: see text] computation complexity for removing RFI of size d where [Formula: see text]. In this work, we investigate two approaches for RFI mitigation, (1) the computationally efficient Lanczos method based on the Quadratic Mean to Arithmetic Mean (QMAM) approach using information from previously-collected data under similar radio-sky-conditions, and (2) an approach using a celestial source as a reference for RFI mitigation. QMAM uses the Lanczos method for finding the Rayleigh–Ritz values of the covariance matrix [Formula: see text], thus, reducing the computational complexity of the overall approach to [Formula: see text]. Our numerical results, using data from the radio observatory Long Wavelength Array (LWA-1), demonstrate the effectiveness of both proposed approaches to remove strong RFI, with the QMAM-based approach still being computationally efficient.

Survey and monitoring of ASKAP’s RFI environment and trends I: Flagging statistics

Abstract We present an initial analysis of Radio Frequency Interference (RFI) flagging statistics from archived Australian SKA Pathfinder (ASKAP) observations for the ‘Survey and Monitoring of ASKAP’s RFI environment and Trends’ (SMART) project. SMART is a two-part observatoryled project combining analysis of archived observations with a dedicated, comprehensive RFI survey. The survey component covers ASKAP’s full 700–1 800 MHz frequency range, including bands not typically used due to severe RFI. Observations are underway to capture a detailed snapshot of the ASKAP RFI environment over representative 24 h periods. In addition to this dedicated survey, we routinely archive and analyse flagging statistics for all scientific observations to monitor the observatory’s RFI environment in near real-time. We use the telescope itself as a very sensitive RFI monitor and directly assess the fraction of scientific observations impacted by RFI. To this end, flag tables are now automatically ingested and aggregated as part of routine ASKAP operations for all science observations, as a function of frequency and time. The data presented in this paper come from processing all archived data for several ASKAP Survey Science Projects (SSPs). We found that the average amount of flagging due to RFI across the routinely used ‘clean’ continuum science bands is 3%. The ‘clean’ mid band from 1 293 to 1 437 MHz (excluding the 144 MHz below 1293 MHz impacted by radionavigation-satellites which is discarded before processing) is the least affected by RFI, followed by the ‘clean’ low band from 742 to 1 085 MHz. ASKAP SSPs lose most of their data to the mobile service in the low band, aeronautical service in the mid band and satellite navigation service in the 1 510–1 797 MHz high band. We also show that for some of these services, the percentage of discarded data has been increasing year-on-year. SMART provides a unique opportunity to study ASKAP’s changing RFI environment, including understanding and updating the default flagging behaviour, inferring the suitability of and calibrating RFI monitoring equipment, monitoring spectrum management compliance in the Australian Radio Quiet Zone – Western Australia (ARQZWA), and informing the implementation of a suite of RFI mitigation techniques.

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.

A Time-Domain Simulation System of MICAP L-Band Radiometer for Pre-Launch RFI Processing Study

Microwave Imager Combined Active and Passive (MICAP), which is a package of active and passive microwave instruments including L/C/K-band radiometers and L-band scatterometer, has been approved to be taken onbord the Chinese Ocean Salinity Mission. The L-band one-dimensional synthetic aperture radiometer (L-Rad) is the key part of MICAP to measure sea surface salinity (SSS). Since radio frequency interference (RFI) is reported as a serious threat to L-band radiometry, the RFI detection and mitigation techniques must be carefully designed before launch. However, these techniques need to be developed based on the knowledge of how RFI affects complex correlation, visibility function, and reconstructed brightness temperature. This paper presents a time-domain signal modeling method for the simulation of interferometric measurement under RFI’s presences, and a simulation system for L-Rad is established accordingly. Several RFI cases are simulated with different RFI types, parameters, and positions; and the RFI characteristics upon L-Rad’s measurement are discussed. The proposed simulation system will be further dedicated to the design of RFI processing strategy onboard MICAP.

Triple Collocation Analysis for Two Error-Correlated Datasets: Application to L-Band Brightness Temperatures over Land

The error characterization of satellite observations is crucial for blending observations from multiple platforms into a unique dataset and for assimilating them into numerical weather prediction models. In the last years, the triple collocation (TC) technique has been widely used to assess the quality of many geophysical variables acquired with different instruments and at different scales. This paper presents a new formulation of the triple collocation (Correlated Triple Collocation (CTC)) for the case of three datasets that resolve similar spatial scales, with two of them being error-correlated datasets. Besides, the formulation is designed to ensure fast convergence of the error estimators. This approach is of special interest in cases such that finding more than three datasets with uncorrelated errors is not possible and the amount of data is limited. First, a synthetic experiment has been carried out to assess the performance of CTC formulation. As an example of application, the error characterization of three collocated L-band brightness temperature (TB) measurements over land has been performed. Two of the datasets come from ESA (European Space Agency) SMOS (Soil Moisture and Ocean Salinity) mission: one is the reconstructed TB from the operational L1B v620 product, and the other is the reconstructed TB from the operational L1B v620 product resulting from application of an RFI (Radio Frequency Interference) mitigation technique, the nodal sampling (NS). The third is an independent dataset, the TB acquired by a NASA (National Aeronautics and Space Administration) SMAP (Soil Moisture Active Passive) radiometer. Our analysis shows that the application of NS leads to TB error reduction with respect to the current version of SMOS TB in 80% of the points in the global map, with an average reduction of approximately 1 K over RFI-free regions and approximately 1.45 K over strongly RFI-contaminated areas.

A Review of RFI Mitigation Techniques in Microwave Radiometry

Radio frequency interference (RFI) is a well-known problem in microwave radiometry (MWR). Any undesired signal overlapping the MWR protected frequency bands introduces a bias in the measurements, which can corrupt the retrieved geophysical parameters. This paper presents a literature review of RFI detection and mitigation techniques for microwave radiometry from space. The reviewed techniques are divided between real aperture and aperture synthesis. A discussion and assessment of the application of RFI mitigation techniques is presented for each type of radiometer.

Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends

Radio frequency interference (RFI) is a major issue in accurate remote sensing by a synthetic aperture radar (SAR) system, which poses a great hindrance to raw data collection, image formation, and subsequent interpretation process. This paper provides a comprehensive study of the RFI mitigation techniques applicable for an SAR system. From the view of spectrum allocation, possible terrestrial and spaceborne RFI sources to SAR system and their geometry are analyzed. Typical signal models for various RFI types are provided, together with many illustrative examples from real measured data. Then, advanced signal processing techniques for removing RFI are reviewed. Advantages and drawbacks of each approach are discussed in terms of their applicability. Discussion on the future trends are provided from the perspective of cognitive, integrated, and adaptive. This review serves as a reference for future work on the implementation of the most suitable RFI mitigation scheme for an air-borne or space-borne SAR system.

Performance Assessment of Time–Frequency RFI Mitigation Techniques in Microwave Radiometry

Radio–frequency interference (RFI) signals are a well-known threat for microwave radiometry (MWR) applications. In order to alleviate this problem, different approaches for RFI detection and mitigation are currently under development. Since RFI signals are man made, they tend to have their power more concentrated in the time–frequency (TF) space as compared to naturally emitted noise. The aim of this paper is to perform an assessment of different TF RFI mitigation techniques in terms of probability of detection, resolution loss (RL), and mitigation performance. In this assessment, six different kinds of RFI signals have been considered: a glitch, a burst of pulses, a wide-band chirp, a narrow-band chirp, a continuous wave, and a wide-band modulation. The results show that the best performance occurs when the transform basis has a similar shape as compared to the RFI signal. For the best case performance, the maximum residual RFI temperature is 14.8 K, and the worst RL is 8.4%. Moreover, the multiresolution Fourier transform technique appears as a good tradeoff solution among all other techniques since it can mitigate all RFI signals under evaluation with a maximum residual RFI temperature of 21 K, and a worst RL of 26.3%. Although the obtained results are still far from an acceptable bias $ 1 K for MWR applications, there is still work to do in a combined test using the information gathered simultaneously by all mitigation techniques, which could improve the overall performance of RFI mitigation.

Characterization and Mitigation of RFI Signals in Radar Depth Sounder Data of Greenland Ice Sheet

Accurate measurements of fast flowing outlet glaciers in Greenland and Antarctica are of vital importance to improve ice-sheet models that predict the ice-sheets' contribution to sea-level rise over the next century. Radars with high sensitivity and advanced processing capabilities are required to sound ice in fast-flowing glaciers. We developed the multichannel coherent radar depth sounder/imager (MCoRDS/I) for ice thickness measurements and 3-D imaging of bedrock over important areas of Greenland and Antarctica. Radio frequency interference (RFI) degrades the sensitivity of the MCoRDS/I system, thus affecting the quality of the data collected. Data from the 2010 Greenland field season exhibited a degraded signal-to-noise ratio (SNR), requiring extensive RFI analysis, investigation, and mitigation for the MCoRDS/I system. Measurements were taken in an electromagnetic interference (EMI) chamber on individual sections of the MCoRDS/I system to isolate the sources of RFI. Then, RFI mitigation techniques were implemented for the offending sections and EMI chamber measurements verified the integrity of the solution prior to the 2011 Greenland deployment. Recorded data from the 2011 Greenland field season also verified that the RFI mitigation resulted in more than 20 dB improvement in the SNR compared to the 2010 Greenland data. The reduction of EMI emissions has also been beneficial to data collection in subsequent deployments.

COMPARISON OF RADIO-FREQUENCY INTERFERENCE MITIGATION STRATEGIES FOR DISPERSED PULSE DETECTION

Impulsive radio-frequency signals from astronomical sources are dispersed by the frequency dependent index of refraction of the interstellar media and so appear as chirped signals when they reach earth. Searches for dispersed impulses have been limited by false detections due to radio frequency interference (RFI) and, in some cases, artifacts of the instrumentation. Many authors have discussed techniques to excise or mitigate RFI in searches for fast transients, but comparisons between different approaches are lacking. This work develops RFI mitigation techniques for use in searches for dispersed pulses, employing data recorded in a "Fly's Eye" mode of the Allen Telescope Array as a test case. We gauge the performance of several RFI mitigation techniques by adding dispersed signals to data containing RFI and comparing false alarm rates at the observed signal-to-noise ratios of the added signals. We find that Huber filtering is most effective at removing broadband interferers, while frequency centering is most effective at removing narrow frequency interferers. Neither of these methods is effective over a broad range of interferers. A method that combines Huber filtering and adaptive interference cancellation provides the lowest number of false positives over the interferers considered here. The methods developed here have application to other searches for dispersed pulses in incoherent spectra, especially those involving multiple beam systems.

RFI mitigation of GNSS signals for radio astronomy: problems and current techniques

Mitigation of man-made radio frequency interference (RFI) is a problem of increasing importance for radio astronomy. Indeed, numerous terrestrial and satellite services of all kinds create lots of electromagnetic signals in a large part of the radio spectrum that are likely to disturb radio astronomical observations. Moreover, the advent of large, highly sensitive radio telescopes such as SKA, LOFAR, etc., will permit the observation of extremely faint and distant radio sources which exhibit large amounts of red shift, hence overlapping with unprotected bands in the radio spectrum. Among various possible causes of RFI, GNSSs have specific characteristics which can be handled appropriately to design efficient mitigation techniques. GNSS signals are generally well documented and the ephemerides of satellites are well known. Therefore, various partially or fully informed methods can be used, which exploit knowledge of the characteristics of the modulations. Adaptive cancellation techniques can also be used that use auxiliary observations coming from additional antennas. Besides, knowing the spatial direction of the disturbing source, spatial filtering and related techniques that can be implemented in antenna arrays are likely to mitigate RFI with minimum knowledge of the GNSS. After recalling some radio astronomy basics, the paper presents a few examples of RFI caused by satellite systems on radio-astronomical observations. Then, we give a brief overview of state-of-the-art RFI mitigation techniques for radio astronomy and we present in some details the principles and results pertaining to some methods that seem particularly appropriate to mitigate RFI arising from GNSS signals. The importance of cooperation between GNSS designers and astronomers is finally pointed out.