Title :
Spaceborne GNSS-R Minimum Variance Wind Speed Estimator
Author :
Clarizia, Maria Paola ; Ruf, C.S. ; Jales, P. ; Gommenginger, Christine
Author_Institution :
Atmos., Oceanic & Space Sci. (AOSS), Univ. of Michigan, Ann Arbor, MI, USA
Abstract :
A Minimum Variance (MV) wind speed estimator for Global Navigation Satellite System-Reflectometry (GNSS-R) is presented. The MV estimator is a composite of wind estimates obtained from five different observables derived from GNSS-R Delay-Doppler Maps (DDMs). Regression-based wind retrievals are developed for each individual observable using empirical geophysical model functions that are derived from NDBC buoy wind matchups with collocated overpass measurements made by the GNSS-R sensor on the United Kingdom-Disaster Monitoring Constellation (UK-DMC) satellite. The MV estimator exploits the partial decorrelation that is present between residual errors in the five individual wind retrievals. In particular, the RMS error in the MV estimator, at 1.65 m/s, is lower than that of each of the individual retrievals. Although they are derived from the same DDM, the partial decorrelation between their retrieval errors demonstrates that there is some unique information contained in them. The MV estimator is applied here to UK-DMC data, but it can be easily adapted to retrieve wind speed for forthcoming GNSS-R missions, including the UK´s TechDemoSat-1 (TDS-1) and NASA´s Cyclone Global Navigation Satellite System (CYGNSS).
Keywords :
Doppler measurement; atmospheric measuring apparatus; atmospheric techniques; regression analysis; remote sensing; satellite navigation; wind; DDM; GNSS-R Delay-Doppler Maps; GNSS-R mission; GNSS-R sensor; Global Navigation Satellite System-Reflectometry; MV wind speed estimator; NASA CYGNSS; NASA Cyclone Global Navigation Satellite System; NDBC buoy wind matchup; RMS error; UK TDS-1; UK TechDemoSat-1; UK-DMC data; UK-DMC satellite; United Kingdom-Disaster Monitoring Constellation satellite; geophysical model function; overpass measurement; partial decorrelation; regression-based wind retrieval; residual errors; spaceborne GNSS-R minimum variance wind speed estimator; Global Positioning System; Satellites; Sea measurements; Sea surface; Wind speed; Delay-Doppler map; global navigation satellite systems (GNSS)-reflectometry; minimum variance (MV) estimator; ocean surface wind speed;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2014.2303831