Generalized Linear Observables for Ocean Wind Retrieval From Calibrated GNSS-R Delay-Doppler Maps

被引:43
|
作者
Rodriguez-Alvarez, Nereida [1 ]
Garrison, James L. [1 ]
机构
[1] Purdue Univ, Dept Aeronaut & Astronaut, W Lafayette, IN 47907 USA
来源
基金
美国国家航空航天局;
关键词
Bistatic radar; delay-Doppler map (DDM); Earth observation; Global Navigation Satellite System-Reflectometry (GNSS-R); Global Positioning System (GPS); ocean remote sensing; wind retrieval; SCATTERED GPS SIGNALS; WAVE-FORMS; SURFACE; SPEED;
D O I
10.1109/TGRS.2015.2475317
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
The Cyclone Global Navigation Satellite System (CYGNSS) mission will use Global Navigation Satellite System-Reflectometry to measure ocean surface winds in and near the hurricane inner core, including regions beneath the eye wall, which could not previously be measured from space due to intense precipitation. The CYGNSS constellation will consist of eight small satellite observatories in 500-km circular orbits at an inclination of similar to 35 degrees. CYGNSS observatories will receive both direct and reflected signals from Global Positioning System satellites. Direct signals will be used both for conventional navigation of the observatory positions and for calibration of the incident signal power. Reflected signals respond to ocean surface roughness, from which wind speed is retrieved. This is observed as changes in a delay-Doppler map (DDM). A generalized observable, which is defined as a linear combination of the DDM samples, is optimized using three different methods: maximum signal-to-noise ratio, minimum variance of the wind speed, and principal component analysis (PCA). Performance of each of these three approaches is compared with each other and with that of the baseline Level-2 retrievals defined for CYGNSS: DDM average, leading edge slope, and the minimum variance combination of both. PCA is found to have the best performance.
引用
收藏
页码:1142 / 1155
页数:14
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