The Microwave Radiometer Technology Acceleration (MiRaTA) is a 3U CubeSat mission sponsored by the NASA Earth Science Technology Office (ESTO). The science payload on MiRaTA consists of a tri-band microwave radiometer and Global Positioning System (GPS) radio occultation (GPSRO) sensor. The microwave radiometer takes measurements of all-weather temperature (V-band, 50-57 GHz), water vapor (G-band, 175-191 GHz), and cloud ice (G-band, 205 GHz) to provide observations used to improve weather forecasting. The Aerospace Corporation's GPSRO experiment, called the Compact TEC (Total Electron Content) and Atmospheric GPS Sensor (CTAGS), measures profiles of temperature and pressure in the upper troposphere/lower stratosphere (∼20 km) and electron density in the ionosphere (over 100 km). The MiRaTA mission will validate new technologies in both passive microwave radiometry and GPS radio occultation: (1) new ultra-compact and low-power technology for multi-channel and multi-band passive microwave radiometers, (2) the application of a commercial off the shelf (COTS) GPS receiver and custom patch antenna array technology to obtain neutral atmospheric GPSRO retrieval from a nanosatellite, and (3) a new approach to spaceborne microwave radiometer calibration using adjacent GPSRO measurements. In this paper, we focus on objective (3), developing operational models to meet a mission goal of 100 concurrent radiometer and GPSRO measurements, and estimating the temperature measurement precision for the CTAGS instrument based on thermal noise. Based on an analysis of thermal noise of the CTAGS instrument, the expected temperature retrieval precision is between 0.17 K and 1.4 K, which supports the improvement of radiometric calibration to 0.25 K.
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http://dx.doi.org/10.1109/JSTARS.2016.2598798 | DOI Listing |
Adv Mater
November 2024
Department of Microwave Engineering, School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, 150001, China.
Characterization of electromagnetic wave polarization states is critical in various applications of materials, biomedical, and imaging. The emergence of metasurfaces opens up the possibility of implementing highly integrated full-Stokes imagers. Despite rapid development, prevailing schemes on metasurface-based full-Stokes imagers require interleaved or cascaded designs, inevitably resulting in performance deterioration, bulky size, and complicating the imaging procedure due to misalignment.
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October 2024
Faculty of Environment, University of Tehran, Tehran, Iran.
Soil moisture (SM) is a critical variable influencing various environmental processes, but traditional microwave sensors often lack the spatial resolution needed for local-scale studies. This study develops a novel stacking ensemble learning framework to enhance the spatial resolution of satellite-derived SM data to 1 km in the Urmia basin, a region facing significant water scarcity. We integrated in-situ SM measurements (obtained using time-domain reflectometry [TDR]), Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer 2 (AMSR2) SM products, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and vegetation indices, precipitation records, and topography data.
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October 2024
Ocean Sciences Division, U.S. Naval Research Laboratory, NASA Stennis Space Center, John C. Stennis Space Center, MS, 39529, USA.
Visible and microwave satellite measurements can provide the global whitecap fraction. The bubble clouds are three-dimensional structures, and a space-based lidar can provide complementary observations of the bubble depth. Here, we use lidar measurements of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite to quantify global bubble depth from the depolarization.
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June 2024
CommSensLab-UPC, Universitat Politècnica de Catalunya-BarcelonaTech, and IEEC/CTE-UPC, 08034 Barcelona, Spain.
Real-Time RFI Detection and Flagging (RT-RDF) for microwave radiometers is a versatile new FPGA algorithm designed to detect and flag Radio-Frequency Interference (RFI) in microwave radiometers. This block utilizes computationally-efficient techniques to identify and analyze RF signals, allowing the system to take appropriate measures to mitigate interference and maintain reliable performance. With L-Band microwave radiometry as the main application, this RFI detection algorithm focuses on the Kurtogram and Spectrogram to detect non-Gaussian behavior.
View Article and Find Full Text PDFBiosensors (Basel)
April 2024
The Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.
Microwave radiometry (MWR) is instrumental in detecting thermal variations in skin tissue before anatomical changes occur, proving particularly beneficial in the early diagnosis of cancer and inflammation. This study concisely traces the evolution of microwave radiometers within the medical sector. By analyzing a plethora of pertinent studies and contrasting their strengths, weaknesses, and performance metrics, this research identifies the primary factors limiting temperature measurement accuracy.
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