Satellite Microwave Remote Sensing Instrument Performance Estimate Using Monte Carlo Simulation

In this paper, we describe a Monte Carlo technique to simulate the active and passive remote sensor observations (normalized ocean radar backscatter, \sigma^{\circ} and brightness temperatures, Tb) and to estimate the resulting wind direction retrieval accuracy. A critical part of the simulation was...

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Bibliographic Details
Published inSoutheastCon 2018 pp. 1 - 5
Main Authors Hossan, Alamgir, Jacobi, Maria, Jones, W.Linwood
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2018
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Summary:In this paper, we describe a Monte Carlo technique to simulate the active and passive remote sensor observations (normalized ocean radar backscatter, \sigma^{\circ} and brightness temperatures, Tb) and to estimate the resulting wind direction retrieval accuracy. A critical part of the simulation was to calculate the satellite/sensor geometry for each point along the orbital ground track. For this, we used the System Tool Kit (STK) orbital analysis software to determine the antenna pointing geometry and instantaneous-field-of-view (IFOV) locations (latitude, longitude, EIA, and azimuth) versus orbit position. Next, these simulated sensor IFOV's were spatially gridded into 0.25°xO.25° boxes and collocated with numerical weather model "nature-run" outputs, to obtain the desired geophysical parameters, namely wind speed and wind direction. Using existing radar and radiometer geophysical model functions (GMF), which relate ocean σ° and Tb with wind speed, relative wind direction, and earth incidence angle, the radar backscatter measurements and radiometer brightness temperatures (AV-H) were simulated, with realistic values of Gaussian noise added. Finally, a maximum likelihood estimation (MLE) procedure was applied to retrieve the wind directions, which were compared to the nature run WD, and the error statistical results are presented.
ISSN:1558-058X
DOI:10.1109/SECON.2018.8479041