Development of Radio Frequency Interference Detection Algorithm for Passive Microwave Remote Sensing

Radio Frequency Interference (RFI) signals are man-made sources that are increasingly plaguing passive microwave remote sensing measurements. RFI is of insidious nature, with some signals low power enough to go undetected but large enough to impact science measurements and their results. With the launch of the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite in November 2009 and the upcoming launches of the new NASA sea-surface salinity measuring Aquarius mission in June 2011 and soil-moisture measuring Soil Moisture Active Passive (SMAP) mission around 2015, active steps are being taken to detect and mitigate RFI at L-band. An RFI detection algorithm was designed for the Aquarius mission. The algorithm performance was analyzed using kurtosis based RFI ground-truth. The algorithm has been developed with several adjustable location dependant parameters to control the detection statistics (false-alarm rate and probability of detection). The kurtosis statistical detection algorithm has been compared with the Aquarius pulse detection method. The comparative study determines the feasibility of the kurtosis detector for the SMAP radiometer, as a primary RFI detection algorithm in terms of detectability and data bandwidth. The kurtosis algorithm has superior detection capabilities for low duty-cycle radar like pulses, which are more prevalent according to analysis of field campaign data. Most RFI algorithms developed have generally been optimized for performance with individual pulsed-sinusoidal RFI sources. A new RFI detection model is developed that takes into account multiple RFI sources within an antenna footprint. The performance of the kurtosis detection algorithm under such central-limit conditions is evaluated. The SMOS mission has a unique hardware system, and conventional RFI detection techniques cannot be applied. Instead, an RFI detection algorithm for SMOS is developed and applied in the angular domain. This algorithm compares brightness temperature values at various incidence angles for a particular grid location. This algorithm is compared and contrasted with other algorithms present in the visibility domain of SMOS, as well as the spatial domain. Initial results indicate that the SMOS RFI detection algorithm in the angular domain has a higher sensitivity and lower false-alarm rate than algorithms developed in the other two domains.Ph.D.Atmospheric and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86308/1/samisra_1.pd

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

The EZIE Way to Measure the Ionospheric Electrojets with a Three-CubeSat Constellation

A recently selected NASA heliophysics mission of opportunity, the Electrojet Zeeman Imaging Explorer (EZIE), will study the electric currents that play a crucial role in the interactions between Earth and the surrounding magnetosphere. The aurora is a spectacular manifestation of these interactions. EZIE consists of three 6U CubeSats flying in a pearls-on-a-string orbit configuration, each carrying a Microwave Electrojet Magnetogram (MEM) instrument. Four beams on each satellite measure polarimetric radiances that contain the magnetic signatures of the intense currents in ionospheric plasmas (electrojets) based on the Zeeman splitting of molecular oxygen thermal emissions. This novel measurement technique allows for the remote sensing of the electrojets at altitudes notoriously difficult to measure in situ. The EZIE constellation will provide, for the first time, measurements with the spatial and temporal resolution required to distinguish between proposed hypotheses for the physical mechanisms behind the auroral and equatorial electrojets. A series of observing system simulation experiments demonstrate how EZIE will explore the impacts of space weather near Earth. Each MEM instrument consists of four compact 118-GHz heterodyne spectropolarimeters, leveraging technologies demonstrated by TEMPEST-D and CubeRRT; the 6U CubeSat bus heritage includes RAVAN, CAT, TEMPEST-D, and CubeRRT. Differential drag maneuvers, akin to those pioneered by CYGNSS and CAT, will be used to manage satellite along-track temporal separation to within 2–10 minutes, eliminating the need for on-board propulsion. EZIE success is possible because of past CubeSat demonstrations and strong commercial partnerships

The Electrojet Zeeman Imaging Explorer (EZIE) Mission and the Microwave Electroject Magnetogram (MEM) Radiometer Instrument

The Electrojet Zeeman Imaging Explorer (EZIE) mission is a multi-satellite 6U CubeSat mission designed to temporally and spatially sample the Earth’s current induced magnetic field. The EZIE mission will help discern amongst competing theories of the spatial structures of Auroral Electro Jets (AEJ). The EZIE mission uses a unique payload design relative to traditional magnetometers; a 118.75 GHz mm-wave polarimetric radiometric system with a digital spectrometer backend, called the Microwave Electrojet Magnetogram (MEM) system. MEM measures the Zeeman split in frequency of the Oxygen absorption line that is directly proportional to the strength of the magnetic field of the observation. The polarimetric nature of MEM helps inform about the direction of the magnetic field. The MEM system consists multiple-beams in a push-broom configuration to detect magnetic fields at a approximate altitude of 80km

Soil Moisture Retrieval with Airborne PALS Instrument over Agricultural Areas in SMAPVEX16

NASA's SMAP (Soil Moisture Active Passive) calibration and validation program revealed that the soil moisture products are experiencing difficulties in meeting the mission requirements in certain agricultural areas. Therefore, the mission organized airborne field experiments at two core validation sites to investigate these anomalies. The SMAP Validation Experiment 2016 included airborne observations with the PALS (Passive Active L-band Sensor) instrument and intensive ground sampling. The goal of the PALS measurements are to investigate the soil moisture retrieval algorithm formulation and parameterization under the varying (spatially and temporally) conditions of the agricultural domains and to obtain high resolution soil moisture maps within the SMAP pixels. In this paper the soil moisture retrieval using the PALS brightness temperature observations in SMAPVEX16 is presented

Soil Moisture ActivePassive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration

The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude. Since April, 2015, the radiometer is under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods including the SMAP L1B TA2TB (from Antenna Temperature (TA) to the Earths surface Brightness Temperature (TB)) algorithm and TA forward models are outlined, and validation approaches to calibration stability/quality are described in this paper including future work. Results show that the current radiometer L1B data satisfies its requirements

The distribution of ammonia on Jupiter from a preliminary inversion of Juno Microwave Radiometer data

The Juno microwave radiometer measured the thermal emission from Jupiter's atmosphere from the cloud tops at about 1 bar to as deep as a hundred bars of pressure during its first flyby over Jupiter (PJ1). The nadir brightness temperatures show that the Equatorial Zone is likely to be an ideal adiabat, which allows a determination of the deep ammonia abundance in the range 362^(+33)_(-33) ppm. The combination of Markov chain Monte Carlo method and Tikhonov regularization is studied to invert Jupiter's global ammonia distribution assuming a prescribed temperature profile. The result shows (1) that ammonia is depleted globally down to 50–60 bars except within a few degrees of the equator, (2) the North Equatorial Belt is more depleted in ammonia than elsewhere, and (3) the ammonia concentration shows a slight inversion starting from about 7 bars to 2 bars. These results are robust regardless of the choice of water abundance