Sidharth Misra

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—A new type of microwave radiometer detector has been developed that is capable of identifying high and low levels of radio-frequency interference (RFI) and of reducing or eliminating its effect on the measured brightness temperatures. High-level, localized RFI can be easily identified by its unnatural appearance in brightness temperature imagery. Low-level(More)
—A new type of microwave radiometer detector that is capable of identifying low-level pulsed radio frequency interference (RFI) has been developed. The Agile Digital Detector can discriminate between RFI and natural thermal emission signals by directly measuring other moments of the signal than the variance that is traditionally measured. The kurtosis is(More)
—A radio-frequency interference (RFI) detection algorithm has been developed for the Aquarius microwave radiometer. The algorithm compares individual brightness temperature samples with a local mean obtained from neighboring samples. If the sample under test significantly deviates from the local mean, then it is assumed to be corrupted by RFI. The algorithm(More)
—In support of the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission, a number of soil moisture and sea salinity campaigns, including airborne L-band radiometer measurements, have been carried out. The radiome-ter used in this context is fully polarimetric and has built-in radio-frequency-interference (RFI)-detection capabilities. Thus,(More)
—Radio frequency interference (RFI) from anthropogenic sources in microwave radiometers detecting geophysical parameters is both common and insidious. As this RFI is always additive to the brightness, the presence of undetected RFI can bias the geophysical parameter retrieval. As radiometers have the most sensitive receivers operating in their band, low(More)
—Two algorithms used in microwave radiometry for radio-frequency interference (RFI) detection and mitigation are the pulse detection algorithm and the kurtosis detection algorithm. The relative performance of the algorithms is compared both analytically and empirically. Their probabilities of false alarm under RFI-free conditions and of detection when RFI(More)
—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 geo-physical parameter retrieval. As microwave radiometers typically have the most sensitive receivers operating in their band,(More)
An inversion algorithm is developed to recover power and duty-cycle of incoming Radio Frequency Interference (RFI) signals from kurtosis. The algorithm applies simulated annealing on multiple kurtosis values obtained from different radiometer integration periods. The paper evaluates the performance of the inversion algorithm by performing Monte-Carlo(More)
—Statistics of radio frequency interference (RFI) observed in the band 1398–1422 MHz during an airborne campaign in the United States are reported for use in analysis and forecasting of L-band RFI for microwave radiometry. The observations were conducted from September to October 2008, and included approximately 92 h of flight time, of which approximately(More)