microwave
A computational experiment has been performed in order to evaluate systematic errors of atmospheric Total Water Vapor (TWV) and integral Liquid Water Content (LWC) microwave radiometric retrieval from satellites by means of dual-frequency method (inverse problem). The errors under consideration may arise due to the non-linearity of brightness temperature level on true liquid water and effective cloud temperature dependencies and due to neglecting the spatial distribution of cumulus clouds in the satellite microwave radiometer antenna field-of-view (FOV).
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This dataset contains approx. 5000 labeled images of marker on Smith Chart of Keysight VNA 9914a. Since smith chart contains "infinity" (although compensated in the device mathematically), the data from Smith Chart window pane is not apt for tuning the all-pole MW filters.
This dataset can be used to track the marker position while tuning the circuitary when considering Image Processing based Filter Tuning. Images are taken from various angles to ensure the robust behaviour and high detection accuracy.
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This dataset is compiled from five years of observation from the Global Precipitation Measurement (GPM) core observatory Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR). Retrieved emissivites and surface backscatter cross sections are gridded at quarter-degree, monthly resolution separately for non-snow-covered land, snow-covered land, and sea ice.
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The proposed signals are used for electromagnetic-based stroke classification. Six realistic head phantom computed from MRI scans, is surrounded by an antenna array of 16 dipole antennas distributed uniformly around the head. These antennas are deployed in a fixed circular array around the head, at a distance of approximately 2-3 mm from the head. A Gaussian pulse covering the bandwidth from 0:7 to 2 GHz is emitted from each of the antennas, sequentially, while all of the antennas capture the scattered signals. Since 16 antennas were used, there are a total of 256 channel signals (i.e.
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