gnss reflectometry for sea surface wind speed estimation

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

PDF

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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