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Effects of CW and modulated interference on baseband of AM and FM demodulators used for control of unmanned scientific satellites
Radio interference from Saturn V launch vehicle fluorescent work lamps
Feasibility of computer prediction of broadband near-field electromagnetic interference in space vehicles
Probability distributions of radio interference on forward scatter of radiation by precipitation
Slotted wind tunnel interference tests on sweptback lifting wings
Preproduction test program for measuring electromagnetic interference and susceptability of high level multicoder
Radio frequency interference and target acquisition probability for radar-telemetry system
Estimating method for lift interference of wing- body combinations at supersonic speeds
Phase correcting networks to compensate for intersymbol interference in digital communications systems
Verification of Kiessig equation for interference fringes formed by X-rays scattered from thin films
Random error estimation for Mach-Zehnder interferometer interference fringe measurements
Idealized antenna patterns for communication satellite interference studies
Calculation method for wind tunnel wall interference velocities for tunnels of arbitrary cross section
Variable ratio DC transformer regulator used in voltage boost configuration of power system in Radio Astronomy Explorer /RAE/ spacecraft, noting RF interference reduction
A microcomputer based software for analysis of radio frequency interference is presented in this paper.
Susceptibility to two types of interfering signals was requested by the SFCG: a pure carrier (single frequency tone)and wide-band RFI (characteristics unspecified). Selecting a broad-band interfering signal is diffuclt because it should represent the types of interference to be found in the space science service bands.
Radio-frequency interference (RFI) is an increasingly serious problem for passive and active microwave sensing of the Earth. To satisfy their measurement objectives, many spaceborne passive sensors must operate in unprotected bands, and future sensors may also need to operate in unprotected bands. Data from these sensors are likely to be increasingly contaminated by RFI as the spectrum becomes more crowded. In a previous paper we reported on a preliminary investigation of RFI observed over the United States in the 6.9-GHz channels of the Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System Aqua satellite. Here, we extend the analysis to an investigation of RFI in the 6.9- and 10.7-GHz AMSR-E channels over the global land domain and for a one-year observation period. The spatial and temporal characteristics of the RFI are examined by the use of spectral indices. The observed RFI at 6.9 GHz is most densely concentrated in the United States, Japan, and the Middle East, and is sparser in Europe, while at 10.7 GHz the RFI is concentrated mostly in England, Italy, and Japan. Classification of RFI using means and standard deviations of the spectral indices is effective in identifying strong RFI. In many cases, however, it is difficult, using these indices, to distinguish weak RFI from natural geophysical variability. Geophysical retrievals using RFI-filtered data may therefore contain residual errors due to weak RFI. More robust radiometer designs and continued efforts to protect spectrum allocations will be needed in future to ensure the viability of spaceborne passive microwave sensing.
The NASA Soil Moisture Active and Passive (SMAP) mission will measure soil moisture with a combination of Lband radar and radiometer measurements. We present an assessment of the expected impact of radio frequency interference (RFI) on SMAP performance, incorporating projections based on recent data collected by the Aquarius and SMOS missions. We discuss the impacts of RFI on the radar and radiometer separately given the differences in (1) RFI environment between the shared radar band and the protected radiometer band, (2) mitigation techniques available for the different measurements, and (3) existing data sources available that can inform predictions for SMAP.