Transcript Simulations and exploitation of GNSS-R signals from a 60

Simulations and exploitation of GNSS-R
signals from a 60-meter lighthouse for
applications in surface hydrology
processes
Nicolas ROUSSEL
Laurent LESTARQUIT
04/05 novembre 2013
PhD advisers: Guillaume RAMILLIEN, Frédéric FRAPPART
Plan
Introduction
Simulations
Field measurements
 Introduction
 Simulations
 Field measurements
 GNSS-based tide gauge system
with SILICOM datalogger
 Analysis of signal-to-noise ratio
(SNR) series
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Space Reflecto – Nicolas ROUSSEL / Laurent LESTARQUIT
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Plan
Introduction
Simulations
Field measurements
 Introduction
 Simulations
 Field measurements
 GNSS-based tide gauge system
with SILICOM datalogger
 Analysis of signal-to-noise ratio
(SNR) series
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Introduction
Introduction
 Ground configuration
Simulations
Field measurements
 Embedded configuration
Source : Institut de Ciències de l’Espai (http://www.ice.csic.es)
Direct/reflected signals correlation
 Position of the specular reflection point
 Altimetry
 Properties of the reflection surface
(roughness)
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Introduction
Introduction
Simulations
Field measurements
- 60 m -
 The Cordouan Lighthouse (45°35’11’’N ; 1°10’24’’O)
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Plan
Introduction
Simulations
Field measurements
 Introduction
 Simulations
 Field measurements
 GNSS-based tide gauge system
with SILICOM datalogger
 Analysis of signal-to-noise ratio
(SNR) series
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Simulations
Introduction
Simulations
Field measurements
Simulator development
 Modeling the trajectories of GNSS electromagnetic waves that are
reflected on the surface of the Earth, based on real ephemeris
 Determine the potential of GNSS-R for mapping the characteristics of the
reflecting surface
 Explore different configurations of performing measurements and
instrument installations:
 variations in the reflectometer height, mask effects due to the terrain,
satellites geometry, ...
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Simulations
Introduction
Simulations
Field measurements
 Determination of the position of the specular reflection points: 3 algorithms
Correctness
- Approximation of the Earth into a local sphere
Computation
speed
- Approximation of the Earth into a local ellipsoid
- DEM (Digital Elevation Model) integration
For further information :
Simulations of direct and reflected waves trajectories for in situ GNSS-R
experiments, submitted in Geosciences Model Development
N. Roussel, F. Frappart, G. Ramillien, C. Desjardins, P. Gegout, F. Pérosanz, R. Biancale
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Simulations
Introduction
4/5 November 2013
Simulations
Field measurements
Space Reflecto – Nicolas ROUSSEL / Laurent LESTARQUIT
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Simulations
Introduction
Simulations
Field measurements
Simulator outputs
 Simulations on the Cordouan lighthouse (45°35’11’’N ; 1°10’24’’O)
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Simulations
Introduction
Simulations
Field measurements
Simulations over a week
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Simulations
Introduction
Simulations
Field measurements
Simulations over a week
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Plan
Introduction
Simulations
Field measurements
 Introduction
 Simulations
 Field measurements
 GNSS-based tide gauge system
with SILICOM datalogger
 Analysis of signal-to-noise ratio
(SNR) series
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Space Reflecto – Nicolas ROUSSEL / Laurent LESTARQUIT
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Plan
Introduction
Simulations
Field measurements
 Introduction
 Simulations
 Field measurements
 GNSS-based tide gauge system
with SILICOM datalogger
 Analysis of signal-to-noise ratio
(SNR) series
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SILICOM Data-logger
Introduction
Simulations
Field measurements
SILICOM Data-Logger
Data Logger
 records and time tags a wide choice of
supported RF GNSS signals
 makes possible the characterization
of the reflected signal and the
development
of
algorithms
for
processing the GNSS-R signals.
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SILICOM Data-logger
Introduction
Simulations
Field measurements
31st may 2013 campaign
Data Logger
 to collect GNSS-R signals,
receiving the direct signal via a
RHCP zenith-looking antenna,
and the reflected signal via a
LHCP nadir-looking antenna
Approx. 25 min of acquisitions, 25 MHz, 8 bits
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SILICOM Data-logger
Introduction
Simulations
Field measurements
Acquisition
 1 ms
 Doppler : [-5000:1:5000] Hz
 Detection of 6 satellites :
-
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PRN12
PRN15
PRN17
PRN24
PRN25
PRN26
In agreement with the simulations
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SILICOM Data-logger
Introduction
Simulations
Field measurements
Acquisition
PRN15 exemple : detection of the initial doppler
Direct signal
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Reflected signal
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SILICOM Data-logger
Introduction
Simulations
Field measurements
Acquisition
PRN15 exemple : detection of the initial delay
Direct signal
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Reflected signal
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SILICOM Data-logger
Introduction
Simulations
Field measurements
Correlation function
Direct signal
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Reflected signal
1 ms
1 ms
100 ms
100 ms
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SILICOM Data-logger
Introduction
Simulations
Field measurements
Correlation function
Direct signal
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Reflected signal
1 ms
1 ms
100 ms
100 ms
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SILICOM Data-logger
Introduction
Simulations
Field measurements
Delay-Doppler Maps
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SILICOM Data-logger
Introduction
Simulations
Field measurements
Tracking
Determination of the C/A pseudo-distance for both direct and reflected signals
 The difference between both gives the extra distance 𝛿d traveled by the
reflected wave
Distance (m)
Differences between direct and reflected paths – C/A PRN12
Time (s)
𝛿d = 2ℎ𝑠𝑖𝑛(𝜖)
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𝜖 : satellite elevation
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SILICOM Data-logger
Introduction
Simulations
Field measurements
Tracking
Satellite Num
𝛿d = 2ℎ𝑠𝑖𝑛(ϵ)
PRN12
Receiver height h (m)
With ϵ the elevation
57,47
PRN15
60,47
PRN17
57,75
PRN24
61,98
PRN25
61,66
PRN26
Direct
signal
Mean
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59,46
59,80 ± 1,92
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Plan
Introduction
Simulations
Field measurements
 Introduction
 Simulations
 Field measurements
 GNSS-based tide gauge system
with SILICOM datalogger
 Analysis of signal-to-noise ratio
(SNR) series
4/5 November 2013
Space Reflecto – Nicolas ROUSSEL / Laurent LESTARQUIT
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Plan
Introduction
Simulations
Field measurements
 Introduction
 Simulations
 Field measurements
 GNSS-based tide gauge system
with SILICOM datalogger
 Analysis of signal-to-noise ratio
(SNR) series
4/5 November 2013
Space Reflecto – Nicolas ROUSSEL / Laurent LESTARQUIT
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SNR data
Introduction
Simulations
Multipath amplitude
Field measurements
phase difference between
the direct signal and the
reflected signal (multipath)
Direct signal amplitude
Larson et al., GPS Sol., 2008
x = sin θ :
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SNR data
Introduction
Simulations
Field measurements
L2 SNR data
2nd order polynom
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SNR data
Introduction
Simulations
Field measurements
L2 SNR data
0 – 40° elevation filtration
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SNR data
Introduction
Simulations
Field measurements
L2 SNR data
 The whole 3 months
time series is currently
being analyzed in order
to make the tide appear
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Thanks for your
attention !