An L-band Radio Frequency Interference (RFI) detection and mitigation testbed for microwave radiometry

Abstract—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. Keywords-Detectors, digital radio, interference suppression, microwave radiometry. I

Wideband Digital Signal Processing Test-Bed for Radiometric RFI Mitigation

Radio Frequency Interference (RFI) is a persistent and growing problem experienced by spaceborne microwave radiometers. Recent missions such as SMOS, SMAP, and GPM have detected RFI in L, C, X, and K bands. To proactively deal with this issue, microwave radiometers must (1) Utilize new algorithms for RFI detection (2) Utilize fast digital back-ends that sample at hundreds of MHz. The wideband digital signal processing testbed (WB-RFI) is a platform that allows rapid development and testing various RFI detection and mitigation algorithms

A Demonstration of the Effects of Digitization on the Calculation of Kurtosis for the Detection of RFI in Microwave Radiometry

Abstract-Microwave radiometers detecting geophysical parameters are very susceptible to radio-frequency interference (RFI) from anthropogenic sources. RFI is always additive to a brightness observation, and so the presence of RFI can bias geophysical parameter retrieval. As microwave radiometers typically have the most sensitive receivers operating in their band, low-level RFI is both significant and difficult to identify. The kurtosis statistic can be a powerful means of identifying some types of low-level RFI, as thermal noise has a distinct kurtosis value of three, whereas thermal noise contaminated even with low-level nonthermal RFI often has other values of kurtosis. This paper derives some benign distortions of the kurtosis statistic due to digitization effects and demonstrates these effects with a laboratory experiment in which a known amount of low-level RFI is injected into a digital microwave radiometer

minimizing estimation error variance using a weighted sum of samples from the soil moisture active passive (SMAP) satellite

The National Aeronautics and Space Administration's (NASA) Soil Moisture Active Passive (SMAP) is the latest passive remote sensing satellite operating in the protected L-band spectrum from 1.400 to 1.427 GHz. SMAP provides global-scale soil moisture images with point-wise passive scanning of the earth's thermal radiations. SMAP takes multiple samples in frequency and time from each antenna footprint to increase the likelihood of capturing RFI-free samples. SMAP's current RFI detection and mitigation algorithm excludes samples detected to be RFI-contaminated and averages the remaining samples. But this approach can be less effective for harsh RFI environments, where RFI contamination is present in all or a large number of samples. In this paper, we investigate a bias-free weighted sum of samples estimator, where the weights can be computed based on the RFI's statistical properties

Design, implementation and verification of CubeSat systems for Earth Observation

In recent years, Earth Observation (EO) technologies have surged in an attempt to better understand the world we live in, and exploit the vast amount of data that can be collected to improve our lives. The field of EO encompasses a broad array of technologies capable of extracting information remotely, in a process called Remote Sensing (RS). CubeSats are causing a revolution in the RS field, and are becoming a really important contribution to it. The lack of testing and preparation are common in CubeSat EO missions due to the low budgets they usually suffer from. A successful CubeSat EO mission must supply the lack of size or funding with properly tested components and environments. In this document, emphasis will be given to preemptive approaches such as studying the performance of Commercial Off-The-Shelf (COTS) Global Positioning System (GPS) receivers and the development of simulators for highly dynamic environments This topic will be expanded upon by introducing the problematic of simulating such signals for testing, and the possible countermeasures to Radio-Frequency Interference (RFI) that threatens the success of the mission. Finally, a new S-Band Ground Station will be built to provide access to this band for future CubeSat missions. All of the above will provide a holistic view on some of the hot challenges that EO faces, and multiple future research paths that open with the recent rise of New Space technologies

Implementation and evaluation of a software defined radio based radiometer

This thesis explores using a software defined radio (SDR) to create a SDR-based radiometer that is capable of performing the same operation as a traditional radiometer and offers additional capabilities not found in traditional radiometers. Traditional radiometer requires careful design to ensure correct operation, by digitizing the RF signal as soon as possible and processing this signal in software, the hardware design of the radiometer can be simplified. Digital radiometers have been explored before, but often use customized components. Software defined radio technology has become more widespread, and affordable Commercial Off The Shelf (COTS) SDRs are now available with high performance. This thesis leverages a COTS SDR technology to implement and evaluate a SDR-based radiometer. This will lower the cost of the radiometer and help make radiometers more accessible to a wider audience. The mapping of the functionality of a traditional radiometer to our proposed SDR-based radiometer is examined. Then an experimental evaluation of the performance between a traditional and SDR-based radiometer is conducted. Additionally this thesis explores how the implemented SDR-based radiometer can help mitigate radio frequency interference

Machine Learning Applied To Global Navigation Satellite System Signal Condition Classification

This thesis focuses on machine learning (ML) techniques applied to global navigation satellite system (GNSS) signal condition classification or Radio Frequency Interference (RFI) in GNSS-Reflectometry (GNSS-R). The thesis consists of three individual research topics, namely, (1) Automatic Detection of Galileo Satellite Oscillator Anomaly By Using A Machine Learning Algorithm, (2) Detection and Mitigation of Radio Frequency Interference in GNSS-R Data and (3) Detection and Classification of Radio Frequency Interference Observed by LEO Satellites Using A Machine Learning Algorithm. Chapter 2 presents a two-stage detection method for Galileo satellite oscillator anomalies and discusses the significance of the results. Chapter 3 addresses the process of detecting and mitigating RFI in GNSS-R signals and analyzes the mitigation performance of the results. Chapter 4 extends the ML classifier from Chapter 2 and applies it to the GNSS-R signal direct signal classification. The detection result of the trained ML model for different types of disturbances, including RFI, oscillator anomaly, and ionosphere disturbance, is demonstrated. The thesis concludes in Chapter 5, which summarizes the three research topics and provides the contribution of the research.</p

Validation of spaceborne and modelled surface soil moisture products with cosmic-ray neutron probes

The scale difference between point in situ soil moisture measurements and low resolution satellite products limits the quality of any validation efforts in heterogeneous regions. Cosmic Ray Neutron Probes (CRNP) could be an option to fill the scale gap between both systems, as they provide area-average soil moisture within a 150–250 m radius footprint. In this study, we evaluate differences and similarities between CRNP observations, and surface soil moisture products from the Advanced Microwave Scanning Radiometer 2 (AMSR2), the METOP-A/B Advanced Scatterometer (ASCAT), the Soil Moisture Active and Passive (SMAP), the Soil Moisture and Ocean Salinity (SMOS), as well as simulations from the Global Land Data Assimilation System Version 2 (GLDAS2). Six CRNPs located on five continents have been selected as test sites: the Rur catchment in Germany, the COSMOS sites in Arizona and California (USA), and Kenya, one CosmOz site in New South Wales (Australia), and a site in Karnataka (India). Standard validation scores as well as the Triple Collocation (TC) method identified SMAP to provide a high accuracy soil moisture product with low noise or uncertainties as compared to CRNPs. The potential of CRNPs for satellite soil moisture validation has been proven; however, biomass correction methods should be implemented to improve its application in regions with large vegetation dynamics

Manifold-Based System for Passive-Active Spectrum Sharing

A feasibility study for an automated scheme for spectrum sharing between passive and active users is presented. The needs of spectrum users can be represented by manifolds in a Euclidean hyperspace called electrospace which has 7 dimensions: frequency (f); Cartesian coordinates (x,y,z); angular coordinates (θ,ø), and time (t). The entire globe is tessellated into geographical areas containing spectrum users, called user domains. Each user domain is recursively tessellated into smaller user domains, or subdomains. A computer cluster, or broker, in each smallest subdomain performs the calculations necessary to determine if a particular user in the subdomain experiences interference. Throughout this thesis, the Chicago Loop (area of 4.09 km2, population ~ 21, 000) is taken to be the representative example of a smallest subdomain. Within each subdomain, the number of users served by a broker is reduced to a manageable number by the process of culling. There are three orders of culling. In first-order culling, subdomain pairs without line of sight and not close enough to mutually interfere are culled, or removed from further consideration for interference calculations. In second-order culling, within each subdomain an intersection test of the electrospace manifolds of all user pairs is performed. User pairs whose manifolds do not intersect are culled. In third-order culling a Friis calculation is performed for all remaining user pairs. The output of third-order culling is an RFI flag bit for each user indicating whether interference is present or not. The computational complexity of first-, second-, and third-order culling calculations was determined. Three representative user classes will be discussed: WiFi access points, Terminal Doppler Weather Radars, and passive EESS satellites. The manifold descriptor language (MDL) for each of the three user classes was described. The computational complexity of broker calculations to determine electrospace parameters from the MDL was determined. Using this complexity and the complexity of culling calculations, the total computational requirements for a broker in a representative subdomain is determined in GFLOPS (Giga Floating Point Operations Per Second)