FR4.T05.1.ppt

N. Pierdicca 1 , L. Guerriero 2 , R. Giusto 1 , M. Brogioni 3 , A. Egido 4 , N. Floury 5 1 DIET - Sapienza Univ. of Rome, Rome, Italy 2 DISP - University of Tor Vergata, Rome, Italy 3 CNR/IFAC, Sesto Fiorentino. Italy 4 Starlab, Barcelona, Spain 5 ESA/ESTEC, Noordwyik, The Netherland GNSS Reflection from Bare and Vegetated Soils: Experimental Validation of an End-to-end Simulator

Content ,[object Object],[object Object],[object Object],[object Object]

LEiMON Project ,[object Object],[object Object],[object Object],The SAM dual pol GNSS-R instrument (by Starlab) LEiMON set up

The LEIMON experiment FDR and TDR soil moisture probes Meteo station Soil roughness profilometer Bare (different roughness) and vegetated fields Plant height and water content

Time serie overview West field with developed plants

|Y | 2 Processed signal power at the receiver vs. delay   and frequency f . P T The transmitted power of the GPS satellite. G T , G R The antenna gains of the transmitting and the receiving instrument. R R , R T The distance from target on the surface to receiving and transmitting antennas. T i The coherent integration time used in signal processing.  Bistatic scattering coefficient  2 The GPS correlation (triangle) function S 2 The attenuation sinc function due to Doppler misalignment dA Differential area within scattering surface area A (the glistening zone). The mean power of received signal vs. delay  and frequency f is modeled by integral Bistatic Radar Equation which includes time delay domain response    ’  and Doppler domain response S 2 ( f’-f ) of the system (Zavorotny and Voronovich, 2000). The Bistatic Radar Equation

The BRE integration ,[object Object],function of point scattering delay function of point looking direction wrt boresight function of incidence direction function of point wrt RX and TX position function of point bistatic angle (zenith and azimuth) function of point scattering Doppler Integrand variables are the coordinates defined on the surface

Local vs global frames ,[object Object],[object Object],[object Object],[object Object],[object Object],z’ x’ y’ TX RX SP= [ x s ,y s ,z s ] ECEFF Earth ellipsoide  i  s =  i Earth surface x z y 

 ° electromagnetic modelling Indefinite mean surface plane with roughness at wavelength scale. Bistatic scattering of locally incident plane waves by AIEM Homogeneous vegetation cover. Attenuation and multiple scattering by a discrete medium (Tor Vergata model) INCOHERENT component COHERENT component Scattering of spherical wave by Kirchoff approxi. (Eom & Fung, 1988) attenuated by vegetation

Polarization synthesis for real antennas ,[object Object],[object Object],[object Object],2 orthogonal electric dipoles  /2 phase shifted x y z P = r,  , 

The signal simulator structure ,[object Object],[object Object],[object Object],E.M. bare soil bistatic  ° model Simulator core E.M. vegetation bistatic  ° model

AIEM vs scattering direction  s ,  s  i =31° m v =20 %  z =1.5 cm l=5 cm H RX =10 km HPBW=120° ,[object Object],[object Object],Azimuth  Azimuth  Zenith  Zenith 

DDM output example DDM’s (delay on the horizontal axes, frequency on the vertical axes) for incoherent (top) and coherent (bottom) component at RHCP (left) and LHCP (right) Spaceborne incoherent airbone incoherent

Peak power output example m v =20 %  z =1.5 cm l=5 cm H RX =10 km V RX =180 m/s Head RX =45° HPBW=120° ,[object Object]

[object Object],[object Object],Leimon data ,[object Object],[object Object],reflected direct

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Simulator reproduces quite well LR signal versus  at incidence angles  ≤45°. Validation: angular trend

[object Object],[object Object],[object Object],[object Object],Theoretical simulations show that incoherent component strongly contributes to total signal when soil is rough. Coherent vs. incoherent: soil coherent total

[object Object],[object Object],RMSE=1.6 dB Bias=-1.4 dB Bare soil overall comparison LR East Side , West Side Bare Soils 10%<SMC<30% 0.6<  z <3cm

RMSE=7.25 dB Bias=6.1 dB ,[object Object],[object Object],[object Object],Bare soil overall comparison RR East Side , West Side

RR underestimation RR August 26th SMC=10%  Z =0.6cm ,[object Object],[object Object],RR April 8th SMC=30%  Z =3cm coherent total

Vegetation o verall comparison Fair correspondence between model and vegetation data (except for largest angle  =55°) June 28, July 10,28 22<SMC<18% PWC=1.2, 3.6, 6.7 kg/m 2

Sensitivity to SMC Black: Leimon data (May) and regression line Blue/ Red : Theoretical simulations, two roughnesses ,[object Object],[object Object]

Sensitivity to vegetation Magenta: Leimon data Green: Theoretical simulations vs. PWC ,[object Object],[object Object]

Coherent vs Incoherent: vegetation At 35°, the coherent component is attenuated by about 1 dB each 1kg/m2, which would predict a large sensitivity to PWC ,[object Object],[object Object]

Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

FR4.T05.1.ppt

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FR4.T05.1.ppt