gnss reflectometry for sea surface wind speed estimation
DESCRIPTION
GNSS REFLECTOMETRY FOR SEA SURFACE WIND SPEED ESTIMATION. D. Schiavulli , F. Nunziata, M. Migliaccio, G. Pugliano Università degli Studi di Napoli “ Parthenope ”. VII Riunione annuale CeTeM – AIT sul Telerilevamento a microonde: Sviluppi scientifici ed implicazioni tecnologiche. OUTLINE. - PowerPoint PPT PresentationTRANSCRIPT
GNSS REFLECTOMETRY FOR SEA SURFACE WIND SPEED
ESTIMATION
D. Schiavulli, F. Nunziata, M. Migliaccio, G. PuglianoUniversità degli Studi di Napoli “Parthenope”
VII Riunione annuale CeTeM – AIT sul Telerilevamento a microonde: Sviluppi scientifici ed implicazioni tecnologiche
OUTLINE
MotivationModelingSimulationExperimentsConclusions
OUTLINE
MotivationModelingSimulationExperimentsConclusions
GNSS Constellations
GNSS are all weather L-band satellite sytems dedicated to navigation purposes:
GNSS Constellations
GNSS are all weather L-band satellite sytems dedicated to navigation purposes:
GPS: 24 satellites
Glonass: 24 satellites
Beidou: 35 satellites (completed 2020)
Galileo: 27 satellites (operative 2020)
GNSS Constellations
The GNSS are designed toprovide Positioning, Velocityand Time (PVT) to an userwith a receiver
GNSS Constellations
The distance satellite-user measuring the Time of Arrival (ToA) of the direct signal, i.e. Line of Sight (LoS). 4 satellites are needed to compute x,y,z and time
The GNSS are designed toprovide Positioning, Velocityand Time (PVT) to an userwith a receiver.
GNSS Signal
GNSS Signal
Pseudo-Random-Noise (PRN) codes:
• zero mean:
• constant envelope
0)( tPRN
1)( 2 tPRN
t t+τct-τc
1
PRN is a sequence of random rectangluar pulses called chips:
• Autocorrelation = 1
• Cross-correlation = 0
GNSS-REFLECTOMETRY
GNSS-REFLECTOMETRY
GNSS Reflectometry (GNSS-R) is an innovative technique that exploits GNSS signals reflected off surfaces as signals of opportunity to infer geophysical information of the reflecting scene.
GNSS-R vs Remote Sensing Missions
GNSS-R vs Remote Sensing Missions
Excellent temporal sampling and global coverage;Long-term GNSS mission life;Cost effectiveness, i.e. only a receiver is needed.
GNSS-R vs Remote Sensing Missions
Excellent temporal sampling and global coverage;Long-term GNSS mission life;Cost effectiveness, i.e. only a receiver is needed.
GNSS satellites coverage Snapshot
GNSS-R Applications
GNSS-R Applications
Soil moisture Ice observation
AltimetrySea surface observation
Sea Surface Observation
Sea Surface Observation
Off shore wind farm Coastal erosion
Weather forecasting Maritime control in harbor areas
OUTLINE
MotivationModelingSimulationExperimentsConclusions
GNSS-R for Sea Surface Observation Model
GNSS-R for Sea Surface Observation Model
Specular reflection dominates this scattering scenario, Geometric Optic (GO) approximation has been used. For smooth surface, e.g. calm see
Tx Rx
Specular Point
GNSS-R for Sea Surface Observation Model
When the sea roughness increases, the transmitted signal is spreaded over the sea surface and different points within the so called Glistening Zone (GZ) contribute to the scattered power
Tx Rx
glistening zoneTx Rx
glistening zone
GNSS-R Geometry Modeling
GNSS-R Geometry Modeling
GNSS-R Geometry Modeling
Nominal Specular Point (SP) is in the origin of axes;
Transmitter and receiver lie in the zy plane;
Points whose scattered wave experiences the same delay lie in an ellippse with Tx and Rx as its foci (iso-range ellipse)
Points whose scattered wave experiences the same frequncy shift lie in an hyperbola (iso-Doppler hyperbola)
The received power is mapped in Delay Doppler Map (DDM)
OUTLINE
MotivationModelingSimulationExperimentsConclusions
GNSS-R Model Simulation
Simulated data are different from real data but are veryImportant:
GNSS-R Model Simulation
Simulated data are different from real data but are veryImportant:
To better understand the scattering scenario
To simulate a complex scenario in a controlled environment
GNSS-R Simulation
GNSS-R SimulationThe received average scattered power is given by:
2
22
222222 )(
)()(4)()()(
),( dRR
fSDTfY o
rtSi
GNSS-R SimulationThe received average scattered power is given by:
WhereTi is the coherent integration timeD is the radiation antenna patternRt and Rr are the distances between Tx-scatterer and Rx-scatterer,
respectivelyΛ(•)S(•) represents the Woodward Ambiguity Function (WAF) is the Fresnel coefficient accounting polarization from RHCP to
LHCP σo is the Normalized Radar Cross Section (NRCS) – Gaussian slopes
2
22
222222 )(
)()(4)()()(
),( dRR
fSDTfY o
rtSi
Woodward Ambiguity Function
Woodward Ambiguity Function
The WAF represents the cross-correlation performed at the receiverbetween the scattered signal and the generated replica, where
Woodward Ambiguity Function
The WAF represents the cross-correlation performed at the receiverbetween the scattered signal and the generated replica, whereAlong the the delay axes, the overlapping of rectangular chips generated
a trianglura shape function:
otherwise
cc
,0,1
Woodward Ambiguity Function
The WAF represents the cross-correlation performed at the receiverbetween the scattered signal and the generated replica, whereAlong the the delay axes, the overlapping of rectangular chips generated
a trianglura shape function:
otherwise
cc
,0,1
Along the Doppler axes a sinc function is generated:
ii
i fTifTfTfS
expsin
For low speed receiver, i.e. airborne or fixed platform, the Doppler effect can be neglected and S(δf) = 1 and 1-D Delay Map is generated.
OUTLINE
MotivationModelingSimulationExperimentsConclusions
Experiments
In this study the potentialities of GPS L1 C/A signal for sea surface wind speed estimation have been investigated and the system sensitivity has been evaluated against:
Experiments
In this study the potentialities of GPS L1 C/A signal for sea surface wind speed estimation have been investigated and the system sensitivity has been evaluated against:
receiver altitude ;Transmitter elevation angle;Wind speed.
Experiments
GNSS-R SIMULATOR
Received waveform
Wind speedReceiver altitudeElevation angle
Experiments
GNSS-R SIMULATOR
Received waveform
Wind speedReceiver altitudeElevation angle
Experiments
GNSS-R SIMULATOR
Received waveform
Wind speedReceiver altitudeElevation angle
Experiments
GNSS-R SIMULATOR
Received waveform
Wind speedReceiver altitudeElevation angle
Experiments
Signal-to-Noise-Ratio has been evaluated as:
Where:
Received power – bistatic link budget Thermal noise
o
rt
irttr RR
GLGGPP
44
2
222
N
r
PPSNR
iN TkBP
Experiments The received triangular-shape waveform is wind dependent
Experiments H = 10 Km elevation angle = 45°
Experiments H = 10 Km elevation angle = 30°
Experiments H = 10 Km elevation angle = 60°
Experiments H = 1 Km elevation angle = 45°
Experiments H = 1 Km elevation angle = 30°
Experiments H = 1 Km elevation angle = 60°
Experiments H = 500 m elevation angle = 45°
Experiments H = 500 m elevation angle = 30°
Experiments H = 500 m elevation angle = 60°
OUTLINE
MotivationModelingSimulationExperimentsConclusions
Conclusions
In this study a different approach to deal with GNSS signals is proposed.
GNSS-R can be seen as a bistatic radar system.Results show that GNSS signals can be succesfully exploited
for remote sensing purposes. The SNR shows that different system configuration can be
exploited but different receivers with different accuracy, i.e. cost, need to be employed.
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