44 research outputs found
Sea state monitoring using coastal GNSS-R
We report on a coastal experiment to study GPS L1 reflections. The campaign
was carried out at the Barcelona Port breaker and dedicated to the development
of sea-state retrieval algorithms. An experimental system built for this
purpose collected and processed GPS data to automatically generate a times
series of the interferometric complex field (ICF). The ICF was analyzed off
line and compared to a simple developed model that relates ICF coherence time
to the ratio of significant wave height (SWH) and mean wave period (MWP). The
analysis using this model showed good consistency between the ICF coherence
time and nearby oceanographic buoy data. Based on this result, preliminary
conclusions are drawn on the potential of coastal GNSS-R for sea state
monitoring using semi-empirical modeling to relate GNSS-R ICF coherence time to
SWH.Comment: All Starlab authors have contributed significantly; the Starlab
author list has been ordered randomly. Submitted to GR
The Eddy Experiment: accurate GNSS-R ocean altimetry from low altitude aircraft
During the Eddy Experiment, two synchronous GPS receivers were flown at 1 km
altitude to collect L1 signals and their reflections from the sea surface for
assessment of altimetric precision and accuracy. Wind speed (U10) was around 10
m/s, and SWH up to 2 m. A geophysical parametric waveform model was used for
retracking and estimation of the lapse between the direct and reflected signals
with a 1-second precision of 3 m. The lapse was used to estimate the SSH along
the track using a differential model. The RMS error of the 20 km averaged
GNSS-R absolute altimetric solution with respect to Jason-1 SSH and a GPS buoy
measurement was of 10 cm, with a 2 cm mean difference. Multipath and retracking
parameter sensitivity due to the low altitude are suspected to have degraded
accuracy. This result provides an important milestone on the road to a GNSS-R
mesoscale altimetry space mission.Comment: All Starlab authors have contributed significantly; the Starlab
Author list has been ordered randoml
The GNSS-R Eddy Experiment II: L-band and Optical Speculometry for Directional Sea-Roughness Retrieval from Low Altitude Aircraft
We report on the retrieval of directional sea-roughness (the full directional
mean square slope, including MSS, direction and isotropy) through inversion of
Global Navigation Satellite System Reflections (GNSS-R) and SOlar REflectance
Speculometry (SORES)data collected during an experimental flight at 1000 m. The
emphasis is on the utilization of the entire Delay-Doppler Map (for GNSS-R) or
Tilt Azimuth Map (for SORES) in order to infer these directional parameters.
Obtained estimations are analyzed and compared to Jason-1 measurements and the
ECMWF numerical weather model.Comment: Proceedings from the 2003 Workshop on Oceanography with GNSS
Reflections, Barcelona, Spain, 200
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Evolving ocean monitoring With GNSS-R: promises in surface wind speed and prospects for rain detection
After developing a wind speed retrieval algorithm, derived
winds from measurements of UK TechDemoSat-1 (TDS-1),
from May 2015 to July 2017, are compared to wind products of Advanced Scatterometer showing a reliable performance, especially during rain events. However, a rain signature in GNSS-R observations, a decrease in the value of
the bistatic radar cross section at low winds, is demonstrated,
which can potentially enable the technique to detect precipitation over oceans induced by low-to-moderate winds. This
phenomenon is investigated and finally characterized as the
rain splash effect altering the ocean surface roughness. To improve the quality of derived winds, a machine learning technique is implemented for the wind speed inversion as a geophysical model function. The trained feedforward neural network shows a significant improvement of 17% in the wind
speed RMSE compared to the LS approach. In the end, one
can conclude that space-borne ocean monitoring is evolving
existing products with a potential for novel geophysical applications
Using DDM asymmetry metrics for wind direction retrieval from GPS ocean-scattered signals in airborne experiments
Reflectometry of signals of opportunity such as those emitted by a global navigation satellite system, known as GNSS-R, has been developed over the past years as a technique with great potential for ocean scatterometry, among other applications. Different approaches have been proposed to use GNSS-R for remote sensing of ocean surface roughness. One of them is based on deriving some descriptor/metric from the measured delay-Doppler map (DDM) and directly relating it to a geophysical property of the scattering surface. For instance, different descriptors have been proposed in the literature to measure the DDM spreading caused by the increase in ocean surface mean square slopes due to surface winds. In this paper, a new descriptor based on the DDM is proposed for wind direction retrieval. This descriptor, designated as the skewness angle 1,skew, measures the asymmetry in the DDM power distribution along the Doppler frequency axis, and it was modeled as a function of wind direction by means of a simulation study. Then, that model was validated using real GNSS-R data from an airborne experiment. After validation, the DDM skewness model was successfully used for wind direction retrieval, with a resulting rms error on the order of 20°Peer Reviewe