Radio frequency interference mitigation in GDSL MIMO systems using adaptive complex narrowband filter banks

Radio astronomical data is increasingly corrupted by human telecommunication activities. It is becoming particularly difficult to work at frequencies between 1100–1300 MHz that are rapidly filling up with satellite navigation signals. Therefore, Radio Frequency Interference (RFI) mitigation becomes an important step in the data processing flow. As to the telescopes based on Antenna array, RFI mitigation can be conducted in spatial domain using the sampled covariance matrix. In this paper, a subspace tracking RFI approach has been proposed based on the power method. The RFI spatial signature estimations provided by the reference antenna are used to initialize the power method to support a faster convergence and more accurate estimation. In addition, the reference antenna sequentially steers at the multiple interferences, thereby acquires new updates of each RFI spatial signature successively. Then, the Interference can be mitigated individually by applying the orthogonal projection. The simulation results validate the effectiveness of the proposed algorithm.

Since autumn 2008 a new L-band 7-Feed-Array receiver is used for an HI 21-cm line survey performed with the 100-m Effelsberg telescope. The survey will cover the whole northern hemisphere comprising both, the galactic and extragalactic sky in parallel. Using state-of-the-art FPGA based digital Fast Fourier Transform spectrometers, superior in dynamic range and temporal resolution, allows to apply sophisticated radio frequency interferences (RFI) mitigation schemes to the survey data. The EBHIS data reduction software includes the RFI mitigation, gain-curve correction, intensity calibration, stray-radiation correction, gridding, and source detection. We discuss the severe degradation of radio astronomical HI data by RFI signals and the gain in scientific yield when applying modern RFI mitigation schemes. For this aim simulations of the galaxy distribution within the local volume (z<0.07) with and without RFI degradation were performed. These simulations, allow us to investigate potential biases and selection effects introduced by the data reduction software and the applied source parametrization methods.

A microwave radiometer specifically designed to detect and mitigate many types of Radio Frequency Interference (RFI) is described. The L-band RFI Detection and Mitigation Testbed (DetMit Testbed) will not be optimized for radiometric observation as much as it is optimized for flexibility in the presence of RFI. While the DetMit Testbed will be a fully functional polarimetric L-band radiometer, the ultimate application of this instrument is not so much brightness measurements as it will be validation of RFI mitigation strategies for employment in future L-band (and other frequency) radiometers. The design approaches for the L-band RFI Detection and Mitigation Testbed are expected to apply to C- band and X-band, and presumably also to other frequencies of interest that experience RFI.

The 3Cat-4 mission aims to demonstrate the capabilities of nano-satellites plus the versatility of a Software Defined Radio for passive Earth Observation. Three different microwave payloads are integrated into a single unit CubeSat platform: a multi-constellation (GPS and Galileo) and a dual-band (L1 and L2) Global Navigation Satellite System - Reflectometer receiver, a total power radiometer including a novel Radio Frequency Interference (RFI) detection and mitigation technique, and an Automatic Identification System receiver for vessels tracking. Being able to validate these technologies in a CubeSat enables their fast adoption as hosted payloads or in more performing dedicated platforms in the future. This paper shows a novel approach for embedding multiple passive microwave payloads in a single platform.

Characteristics of L-band radio frequency interference detected via the soil moisture active passive radiometer in China and its offshore areas

The detection performance of high-frequency surface wave radar (HFSWR) is highly susceptible to radio frequency interference (RFI). The fact that external RFIs will turn into a chirp signal and the fractional Fourier transform (FRFT) is a potent tool to analyze the chirp signal, motivates us to use FRFT in interference mitigation. In this letter, two new RFI suppression schemes are proposed, of which one is based on hybrid used of FRFT and autoregressive (AR) linear prediction algorithm, another is based on joint FRFT and recursive least squares (RLS) adaptive filtering algorithm. The simulation result indicates that the proposed schemes can effectively mitigate external RFIs even when the interferences cover Bragg peaks. The experimental result shows that the proposed schemes can effectively suppress RFI without losing echoes, and the signal to noise-plus-interference ratio is improved by 6 dB on average after RFI suppression.

Detection and mitigation of radio frequency interference (RFI) is the first and also the key step for data processing in radio observations, especially for ongoing low frequency radio experiments towards the detection of the cosmic dawn and epoch of reionization (EoR). In this paper we demonstrate the technique and efficiency of RFI identification and mitigation for the 21 Centimeter Array (21CMA), a radio interferometer dedicated to the statistical measurement of EoR. For terrestrial, man-made RFI, we concentrate mainly on a statistical approach by identifying and then excising non-Gaussian signatures, in the sense that the extremely weak cosmic signal is actually buried under thermal and therefore Gaussian noise. We also introduce the so-called visibility correlation coefficient instead of conventional visibility, which allows a further suppression of rapidly time-varying RFI. Finally, we briefly discuss removals of the sky RFI, the leakage of sidelobes from off-field strong radio sources with time-invariant power and a featureless spectrum. It turns out that state of the art technique should allow us to detect and mitigate RFI to a satisfactory level in present low frequency interferometer observations such as those acquired with the 21CMA, and the accuracy and efficiency can be greatly improved with the employment of low-cost, high-speed computing facilities for data acquisition and processing.

In view of the inconsistency of channel gains and a large amount of interference noise in Solar Broadband Radio Spectrometer (SBRS) observation data, they will seriously affect the analysis of SBRS data. In this paper, a method of Radio Frequency Interference (RFI) detection and mitigation for SBRS observation data is reported. Firstly, the SBRS observation data are preprocessed, a part of the observation data was selected to calculate the mean and variance to achieve the normalization of the entire observation data, which can avoid the influence of strong noise on the normalization result. Furthermore, we proposed an adaptive threshold RFI detection method based on fusion wavelet transform reconstruction and an RFI elimination method based on neighborhood weighted filling. It is worth mentioning that to detect RFI interference signals of different magnitudes, we adopted an iterative approach to the RFI detection and mitigation process. Through qualitative analysis of real observation data and quantitative analysis of simulated data, it is shown that the method proposed in this paper can effectively eliminate RFI in SBRS observation data, and improve the quality of observation data for further scientific analysis.

Aquarius is an L-band active/passive sensor designed to globally map sea surface salinity from space [1, 2]. Two instruments, a radar scatterometer and a radiometer, observe the same surface footprint almost simultaneously. The radiometer is the primary instrument for sensing sea surface salinity (SSS), while the scatterometer is included to provide a correction for sea surface roughness, which is a primary source of error in the salinity retrieval. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. An important feature of the data processing includes detection and mitigation of Radio Frequency Interference (RFI), which is done separately for both active and passive instruments. Correcting for RFI is particularly critical over ocean because of the high accuracy required in the brightness temperature measurements for SSS retrieval. It is also necessary for applications of the Aquarius data over land, where man-made interference is widespread, even though less accuracy is required in this case. This paper will provide an overview of the current status of the Aquarius RFI processing and an update on the ongoing work on the improvement of the RFI detection and mitigation performance.

Initial examination of ALOS PALSAR synthetic aperture radar (SAR) data has indicated significant radio frequency interference (RFI) in several geographic locations around the world. RFI causes significant reduction in image contrast, introduces periodic and quasi-periodic image artifacts, and introduces significant phase noise in repeat-pass interferometric data reduction. The US National Research Council Decadal Survey of Earth Science has recommended DESDynI, a Deformation, Ecosystem Structure, and Dynamics of Ice satellite mission comprising an L-band polarimetric radar configured for repeat-pass interferometry. There is considerable interest internationally in other future L-band and lower frequency systems, as well. Therefore, the issues of prevalence and possibilities of mitigation of RFI in these crowded frequency bands are of considerable interest. RFI is observed in ALOS PALSAR in California and Hawaii, USA, and in southern Egypt in data examined to date. Application of several techniques for removing it from the data prior to SAR image formation, ranging from straight-forward spectral normalization to time-domain, multi-phase filtering techniques, are considered. Considerable experience has been gained from the removal of RFI from P-band acquired by the GeoSAR system. These techniques applied to the PALSAR data are most successful when the bandwidth of any particular spectral component of the RFI is narrow. Performance impacts for SAR imagery and interferograms are considered in the context of DESDynI measurement requirements.

Quadrupole resonance (QR) technology for explosives detection is of crucial importance in an increasing number of applications. For landmine detection, where the detection system cannot be adequately shielded, QR has proven to be highly effective if the QR sensor is not exposed to radio frequency interference (RFI). However, strong non-Gaussian RFI in the field is unavoidable, making RFI mitigation a critical part of the signal processing. In this paper, a statistical model of the non-Gaussian RFI is presented. The QR model is used within the context of an adaptive filtering methodology to mitigate RFI, and this approach is compared to other RFI mitigation techniques. Results obtained using both simulated and measured QR data are presented.

Ultra-wideband (UWB) Synthetic Aperture Radars (SAR) operate over a large bandwidth ranging from under 100 MHz to over a few Ghz. They often share spectrum with other systems such as radio, TV and cellular networks. The mitigation of radio frequency interference(RFI) from these sources is an important problem for UWB SAR systems. Traditional RFI suppression techniques such as notch filtering introduce side effects such as large sidelobes or poor peak-to-sidelobe ratio. More recently, methods based on sparsity and compressive sensing that do not have these side effects have been proposed. In particular, a sparse and low-rank method that models SAR data as a linear combination shifted SAR pulses and RFI to be of low-rank has been found to be effective. This model however uses the structure of SAR data in down-range direction only and ignores the structure in azimuth direction. In this paper, we propose to replace the data model with a new sparse model that incorporates structure in azimuth direction as well. We demonstrate that the new model has significantly better performance than the previously proposed model. It performs robustly even in the presence of high level of noise(-20 dB SNR) and does not suppress small targets like the previously proposed model did.

Radio Frequency Interference (RFI) is a growing problem in Synthetic Aperture Radar (SAR). The choice of operational frequency of remote sensing instruments is dictated by the physics of the parameters that are to be observed. On the other hand, the frequency spectrum becomes more crowded with the increasing demand for wireless services. This requires cohabitation of multiple systems at the same or neighbouring frequency bands. As a result, RFI can introduce artefacts and degrade the derived SAR products. A mitigation of RFI is critical. New removal techniques can be implemented with Digital Beamforming (DBF) radars. In this paper, we present a Pulse and Range-Dependent Time Minimum Variance Distortionless Response (PRDTMVDR) Beamformer. The antenna pattern (AP) is adaptively changed for each pixel based on the inherent imaging geometry of SAR and thus the RFI suppression is improved compared to an AP that is fixed for the pulse duration.

Various methods of radio frequency interference (RFI) mitigation methods at radio astronomy tele- scopes are being considered. Special attention is given to real-time processing algorithms. Computer simulations and observational results are used to describe the applicability of these methods. Best results can be achieved when the RFI mitigation procedures are adapted to the particular radio telescope, the type of observations, and the peculiarities of the RFI environment. A combination of dierent linear and non-linear methods in the tem- poral and frequency domains, with and without the use of reference antennas, may give considerable suppression of strong RFI.

Radio Frequency Interference (RFI) is a significant limiting factor in the retrieval of geophysical parameters measured by microwave radiometers. Microwave Imager Combined Active and Passive (MICAP), which is a package of active and passive microwave instruments including L/C/K-band Microwave Interferometric Radiometer (MIR) and L-band scatterometer, has been approved to be taken on-board in the Chinese Ocean Salinity Mission. RFI is a serious threat to MICAP, especially to the L-band MIR. In the first part of this paper, RFI mitigation strategy combined on-board processing and on-ground processing is proposed based on MICAP structure. Secondly, RFI side lobe blanking criteria is proposed to clarify the requirements for on-board RFI detection capabilities, which indicate a trade-off between detection sensitivity and false alarm rate. Thirdly, a verification experiment of RFI mitigation method is demonstrated for on-board RFI detection.