Spaceborne GNSS-R Minimum Variance Wind Speed Estimator

被引:227
作者
Clarizia, Maria Paola [1 ,2 ]
Ruf, Christopher S. [1 ]
Jales, Philip [3 ]
Gommenginger, Christine [4 ]
机构
[1] Univ Michigan, Ann Arbor, MI 48109 USA
[2] Natl Oceanog Ctr, Southampton SO14 3ZH, Hants, England
[3] Surrey Satellite Technol Ltd, Guildford GU2 7YE, Surrey, England
[4] Natl Oceanog Ctr, Southampton SO14 3ZH, Hants, England
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2014年 / 52卷 / 11期
基金
英国自然环境研究理事会;
关键词
Delay-Doppler map; global navigation satellite systems (GNSS)-reflectometry; minimum variance (MV) estimator; ocean surface wind speed; VECTOR RETRIEVAL ALGORITHM; GEOPHYSICAL MODEL FUNCTION; OCEAN SURFACE; GPS SIGNALS; NAVIGATION; SCATTERING; ASCAT;
D O I
10.1109/TGRS.2014.2303831
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
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).
引用
收藏
页码:6829 / 6843
页数:15
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