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Simulation of interference between Earth stations and Earth-orbiting satellites

It is often desirable to determine the potential for radio frequency interference between earth stations and orbiting spacecraft. This information can be used to select frequencies for radio systems to avoid interference or it can be used to determine if coordination between radio systems is necessary. A model is developed that will determine the statistics of interference between earth stations and elliptical orbiting spacecraft. The model uses orbital dynamics, detailed antenna patterns, and spectral characteristics to obtain accurate levels of interference at the victim receiver. The model is programmed into a computer simulation to obtain long-term statistics of interference. Two specific examples are shown to demonstrate the model. The first example is a simulation of interference from a fixed-satellite earth station to an orbiting scatterometer receiver. The second example is a simulation of interference from earth-exploration satellites to a deep-space earth station.

Bishop, D. F.↗

Fiber-optic proximity sensor

Proximity sensor for mechanical hand of remote manipulator incorporates fiber optics to conduct signals between light source and light detector. Fiber optics are not prone to noise from electromagnetic interference and radio-frequency interference as are sensors using long electrical cables.

Bejczy, A. K.↗

RFI and Remote Sensing of the Earth from Space

Passive microwave remote sensing of the Earth from space provides information essential for understanding the Earth's environment and its evolution. Parameters such as soil moisture, sea surface temperature and salinity, and profiles of atmospheric temperature and humidity are measured at frequencies determined by the physics (e.g. sensitivity to changes in desired parameters) and by the availability of suitable spectrum free from interference. Interference from manmade sources (radio frequency interference) is an impediment that in many cases limits the potential for accurate measurements from space. A review is presented here of the frequencies employed in passive microwave remote sensing of the Earth from space and the associated experience with RFI.

RFI↗

OAST Space Theme Workshop. Volume 2: Theme summary. 3: Search for extraterrestrial intelligence (no. 9). A: Theme statement. B. 26 April 1976 presentation. C. Summary. D. Newer initiatives (form 4). E. Initiative actions (form 5)

Preliminary (1977-1983), intermediate (1982-1988), and long term (1989+) phases of the search for extraterrestrial intelligence (SETI) program are examined as well as the benefits to be derived in radioastronomy and the problems to be surmounted in radio frequency interference. The priorities, intrinsic value, criteria, and strategy for the search are discussed for both terrestrial and lunar-based CYCLOPS and for a space SETI system located at lunar liberation point L4. New initiatives related to antenna independent technology, multichannel analyzers, and radio frequency interference shielding are listed. Projected SETI program costs are included.

Source record↗

RFI Detection and Mitigation using Independent Component Analysis as a Pre-Processor

Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Soil Moisture and Ocean Salinity (SMOS), Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

independent component analysis↗

RINGSAT

Radio frequency interference (RFI) presents a serious problem to naval communications. Unauthorized transmissions on the same frequencies that FLTSAT or LEASAT use cause a loss of one or more transponders on a satellite. The problem is not correctable until the emitter is located and turned off, or until it runs off on its own. The present geolocation system cannot deal with the RFI problem adequately. This causes the Navy to lose operational capability and money. The proposed Radio Frequency Interference Navy Geolocation Satellite (RINGSAT) would locate the source of the interference within 3 hours, an outstanding improvement over current equipment. Furthermore, RINGSAT can be built quickly, at minimal cost, and can be used concurrently for other military missions. Currently, geolocation to identify the RFI is done at Naval Space Command. Using single satellite doppler, time delay of arrival, and frequency delay of arrival techniques, it is possible to locate the interfering emitter. However, for the first quarter of fiscal year 1993, about 50 different channels used by the Navy were nonoperational for over 500 hours. Almost 30 percent of the interference occurrences lasted for over 12 hours. In only one quarter of the cases was the interference turned off in less than two_hours either by our detection or on its own.

DOWDY↗

Radio interference in the near-earth environment

Natural and man-made radio frequency interference (RFI) are potentially serious obstacles to the successful operation of an array of spacecraft used for low frequency (1 to 30 MHz) radio interferometry in the near-earth environment. Several satellites and planetary probes have carried radio astronomy experiments, and the moderate data base that they provide are examined to help understand the near-earth RFI environment. The general conclusion is that the region of space within 100 earth-radii of the earth is a hostile environment for any radio astronomy experiment. If a low frequency array in earth orbit is to yield useful astronomical results, severe interference problems must be anticipated and overcome. A number of recommendations are made to further examine the feasibility of such an array.

Erickson, W. C.↗

A Case Study in RFI at L-band Detected by SMAP

Even when radio frequency interference (RFI) is detected, very little is known about the sources of the interference. More information about the sources would facilitate the design of systems to deal with the interference. Reporting of interference by the RFI teams for SMAP and SMOS through international channels has resulted in a decrease in RFI and identification of several sources. Two such cases that have been identified in the USA and are reported here.

Radiometry↗

Development of RFI Mitigation Techniques with Digital Beamforming

Remote sensing radars with longer wavelengths penetrate deeper into the observed scene and are more suitable for the scientific observation of ice sheets or vegetation. Therefore, SAR systems are moving to lower frequencies like L- or P-band. However, as the frequency spectrum is a limited resource, this means that the occupied frequency band has to be shared with existing users. These users can have serious impact on the imaging quality. Radio frequency interference (RFI) that arrives at the antenna together with the SAR backscatter is causing a drop of the signal-to-noise ratio. Despite the high processing gain of the SAR signal, artifacts can appear in the image if the RFI is strong enough. This can lead to a corruption of the acquired data and make it unsuitable for scientific purposes. Hence, the investigation of methods for RFI mitigation is critical to the performance of radar missions and to ensure they meet their main task.

Digital Beamforming↗

Adaptive Antenna Pattern Notching of Interference in Synthetic Aperture Radar Data Using Digital Beamforming

Radio Frequency Interference (RFI) is a growing problem in Synthetic Aperture Radar (SAR)systems as scientific motivations push the radars to lower frequencies and as more wireless services share the frequency spectrum. New, advanced SAR instruments, such as NASA's EcoSAR, DBSAR and DLR's Tandem-L mission, employ a multichannel architecture capable of Digital Beamforming (DBF). Radars with DBF are capable of notching the antenna pattern in specific directions, which can be utilized to suppress RFI on board or in post-processing. A well-researched beamformer for this purpose is the Minimum Variance Distortionless Response (MVDR) Beamformer. However, the number of interferers that can be removed through notching is limited by the number of receive channels. It is therefore essential to adaptively change the antenna pattern notching throughout the image in time and frequency for the best results with a given number of receive channels. In this paper, we present several methods to achieve this notching by making use of the spatial SAR signal distribution in range time, range frequency, azimuth time and azimuth Doppler that is inherent to the SAR imaging geometry. Because this distribution is time-variable and yet predictable, it can be used to improve the angle of arrival estimation of the RFI and the adaptive notching. The presented methods can be applied to a Digital Beamforming (DBF) SAR signal with multiple channels in elevation and/or in azimuth. Simulations show that the proposed methods increase the ability to notch out-of-swath interference from multiple directions and lessen the impact on in-swath interference. The improvement of the interferometric coherence for a single-pass interferogram acquired by NASA's EcoSAR system (capable of DBF in elevation) is demonstrated. The removal of periodic RFI artifacts is achieved.

RFI↗

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization problems that encompasses, among many others, the problem of generating optimal space-data communications schedules.

ground stations↗

SMAP Mission: Changes in the RFI Environment

The Soil Moisture Active/Passive satellite microwave radiometer has been providing measurements of L-band thermal emission from Earth for more than 2 years. SMAP retrieves surface soil moisture from its brightness temperature measurements, and continues to provide science products to the user community. Even though the SMAP radiometer operates in a protected band, its measurements are still corrupted by Radio Frequency Interference (RFI) caused by illegal in-band transmissions or out-of-band emissions. The SMAP radiometer was designed to include special hardware to enable RFI detection and filtering using multiple detection algorithms. Given the good overall performance of SMAP algorithms to detect RFI sources, an automatic tool to report source properties automatically was developed and is now operational. This paper provides a preliminary analysis of the outputs of this reporting tool with a particular focus on the evolution of the RFI environment observed by SMAP during its period of operations.

L-band↗

Microwave Radiometer RFI Detection Using Deep Learning

Radio frequency interference (RFI) is a risk for microwave radiometers due to their requirement of very high sensitivity. The Soil Moisture Active Passive (SMAP) mission has an aggressive approach to RFI detection and filtering using dedicated spaceflight hardware and ground processing software. As more sensors push to observe at larger bandwidths in unprotected or shared spectrum, RFI detection continues to be essential. This article presents a deep learning approach to RFI detection using SMAP spectrogram data as input images. The study utilizes the benefits of transfer learning to evaluate the viability of this method for RFI detection in microwave radiometers. The well-known pretrained convolutional neural networks, AlexNet, GoogleNet, and ResNet-101 were investigated. ResNet-101 provided the highest accuracy with respect to validation data (99%), while AlexNet exhibited the highest agreement with SMAP detection (92%).

Microwave radiometry↗

RFI Mitigation and Detection for the SMAP Radar

The planned Soil Moisture Active Passive (SMAP) mission will use both active radar and passive radiometer instruments at L-Band to measure and monitor both soilmoisture and freeze/thaw state globally. The frequency band allocated for the SMAP radar is shared with the Global Navigation Satellite Systems and ground-basedradiolocation services. Signals from those users present significant sources of anthropogenic radio frequency interference (RFI) which contaminate the radarmeasurements. To mitigate RFI, the radar is designed with tunable operating frequency, which allows the center frequency to be tuned to avoid RFI. The filtering scheme in the receiver is configured to get a high level of RFI suppression. To meet the high accuracy measurement requirements, RFI detection and correction will be required during ground data processing. Some candidate algorithms have been evaluated, and they have been tested against simulated SMAP data derived from the PALSAR data.

Soil Moisture Active Passive (SMAP)↗

Recent Advances in SMAP RFI Processing

The measurements made by the Soil Moisture Active/Passive (SMAP) mission are affected by the presence of Radio Frequency Interference (RFI) in the protected 1400-1427 MHz band. In SMAP data processing, the main protection against RFI is a sophisticated RFI detection algorithm which flags sub-samples in time and frequency that are contaminated by RFI and removes them before estimating the brightness temperature. This contribution presents two additional approaches that have been developed to address the RFI concern in SMAP. The first consists in locating sources of RFI; once located, it becomes possible to report RFI sources to spectrum management authorities, which can lead to less RFI being experienced by SMAP in the future. The second is a new RFI detection method that is based on detecting outliers in the spatial distribution of measured antenna temperatures.

Radio Frequency Interference↗

Design and Development of the SMAP Microwave Radiometer Electronics

The SMAP microwave radiometer will measure land surface brightness temperature at L-band (1413 MHz) in the presence of radio frequency interference (RFI) for soil moisture remote sensing. The radiometer design was driven by the requirements to incorporate internal calibration, to operate synchronously with the SMAP radar, and to mitigate the deleterious effects of RFI. The system design includes a highly linear super-heterodyne microwave receiver with internal reference loads and noise sources for calibration and an innovative digital signal processor and detection system. The front-end comprises a coaxial cable-based feed network, with a pair of diplexers and a coupled noise source, and radiometer front-end (RFE) box. Internal calibration is provided by reference switches and a common noise source inside the RFE. The RF back-end (RBE) downconverts the 1413 MHz channel to an intermediate frequency (IF) of 120 MHz. The IF signals are then sampled and quantized by high-speed analog-to-digital converters in the radiometer digital electronics (RDE) box. The RBE local oscillator and RDE sampling clocks are phase-locked to a common reference to ensure coherency between the signals. The RDE performs additional filtering, sub-band channelization, cross-correlation for measuring third and fourth Stokes parameters, and detection and integration of the first four raw moments of the signals. These data are packetized and sent to the ground for calibration and further processing. Here we discuss the novel features of the radiometer hardware particularly those influenced by the need to mitigate RFI.

radio frequency interference↗

Interference Mitigation Using Cyclic Autocorrelation and Multi-Objective Optimization

Radio frequency interference on space-to-ground communications links can degrade performance and disrupt the transfer of critical data. These interference events become increasingly likely as more users enter the spectrum, due in part to shared spectrum allocations and scheduling conflicts. If this interference could be detected and mitigated by an automated system, then link performance and reliability in these scenarios could be improved. This report describes the implementation and evaluation of an automated interference mitigation system that provides this functionality. The system uses Cyclic Autocorrelation (CAC) signal processing techniques to monitor the spectrum and detect interfering signals, and it applies a multi-objective optimization approach to mitigate interference by changing link parameters to continuously optimize the link. The implementation was evaluated to characterize its signal detection capabilities for various link qualities and to compare its link management performance to Adaptive Coding and Modulation (ACM) and Constant Coding and Modulation (CCM) when in the presence of randomized interference. In the latter evaluation, the interference mitigation system achieved the highest average throughput in each tested scenario. With these results, the proposed solution provides the groundwork for further automated link management capabilities and continued investigation into interference mitigation approaches.

Interference mitigation↗