POTENTIALS OF A COMPACT POLARIMETRIC SAR SYSTEM

My-Linh Truong-Loï, ONERA/CNES/IETRPascale Dubois-Fernandez, ONERAEric Pottier, IETR – UMR CNRS 6164

Anthony Freeman, JPLJean-Claude Souyris, CNES

IGARSS 20102

Objectives

Missions dedicated to global environmental

change monitoring

Low frequency

radar

Ionosphere interaction Faraday

rotation Compact polarimetry

Transmitting a circular

polarized wave

No depolarization anymore

Receiving two orthogonal

polarized waves

Estimate Faraday rotation

High power of

penetration

Dual-pol system

Large swath

Dual-pol system

IGARSS 20103

Outline

• Background – compact polarimetry

• Faraday rotation estimate• Bare soil surfaces selection• Faraday rotation estimate

• PolSAR applications• Soil moisture estimate• Biomass estimate

• PolInSAR applications• Forest height estimate

• Calibration

IGARSS 20104

Background - Compact Polarimetry 1/2

• π/4 mode: one transmission at 45° and two orthogonal receptions (linear H & V, circular right & left,…)

• π/2 mode: one circular transmission and two orthogonal receptions (linear H & V, circular right & left,…)

• Hybrid polarity : particular case of π/2 : one circular transmission and two linear receptions (H&V)

1

2

11 1

2 2HH VH HH VH

HV VV HV VV

S S S jSkk

S S S jSk j

IGARSS 2010

• π/4-mode potentials: reconstruction of the PolSAR information (1)• Iterative algorithm based on:

• Reflection symmetry• Coherence between co-polarized channels

• π/2-mode potentials: avoid Faraday rotation in transmission (2)• Transmit a circular polarized wave• Adaptation of the reconstruction of the PolSAR information is possible

• Hybrid polarity potentials: decomposition of natural targets (3)• m-δ method based on Stokes parameters

Background - Compact Polarimetry 2/2

(1) J-C. Souyris, P. Imbo, R. FjØrtoft, S. Mingot and J-S. Lee, Compact Polarimetry Based on Symmetry Properties of Geophysical Media : The π/4 Mode, IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 3, Mars 2005.

(2) P. C. Dubois-Fernandez, J-C. Souyris, S. Angelliaume et F. Garestier, The Compact Polarimetry Alternative for Spaceborne SAR at Low Frequency, IEEE Transactions on Geoscience and Remote Sensing, vol. 46, no. 10, Octobre 2008.

(3) R. K. Raney, Hybrid-Polarity SAR Architecture, IEEE Transactions on Geoscience and Remote Sensing, vol. 45, no. 11, Novembre 2007.

IGARSS 20106

Conclusion

• π/2 mode is required for low frequency spaceborne radar

How to estimate/correct for Faraday rotation in reception ?

Bare soil surfaces are first required

IGARSS 20107

The conformity coefficient

Double-bounce Volume Surface

SHV ~ 0

SHH, SVV correlated

Arg<SHHSVV*> ≈ 180°

-1< μ< t2

SHV is significant

SHH, SVV less correlated

t2< μ<t1

SHV ~ 0

SHH, SVV correlated

Arg<SHHSVV*> ≈ 0

t1<μ<1

222

2*

**

*

2

)Re(2

Im2

VVHVHH

HVVVHH

RVRVRHRH

RVRH

SSS

SSS

MMMM

MM

• This coefficient• Can be shown to be FR independent• can be used with CP data as well as FP data• discriminates 3 different types of scattering

M-L. Truong-Loï, A. Freeman, P. C. Dubois-Fernandez and E. Pottier, Estimation of Soil Moisture and Faraday Rotation From Bare Surfaces Using Compact Polarimetry, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 11, Novembre 2009.

IGARSS 20109

Conformity coefficient vs Cloude-Pottier and Freeman-Durden classifications, RAMSES P-band data over St Germain d’Esteuil, France

Conformity coefficientCloude-Pottier classification Freeman-Durden classification

VolumeDouble-bounce Surface

S. R. Cloude et E. Pottier, A Review of Target Decomposition Theorems in Radar Polarimetry, IEEE Transactions on Geoscience and Remote Sensing, vol. 34, no. 2, Mars 1996.

A. Freeman et S. L. Durden, A Three-Component Scattering Model for Polarimetric SAR Data, IEEE Transactions on Geoscience and Remote Sensing, vol. 36, no. 3, Mai 1998.

•Pv > 0.6 Pd & Pv > 0.3 Ps

•Ps>Pd

•Pd

IGARSS 201010

Conclusion

• π/2 mode is required for low frequency spaceborne radar• Introduction of a parameter : the conformity coefficient

• Is FR-independent• Allows to distinguish 3 types of scattering

We can select bare soil surfaces with compact-pol data

Is it now possible to correct for FR with compact-pol data ?

IGARSS 201011

Flow diagram of the process

e

FP calibrated data (Ramses, PALSAR)

Select bare surfaces(by using the conformity coefficient)

Estimate the Faraday rotation

Synthesized CP data (add Faraday rotation)

(1) (2)

(3)

*1arg mod

2 2RR RLM M

*

* *

1arctan 2 mod

2 4RH RV

RV RV RH RH

e M M

M M M M

*arg mod2RH RVS S

IGARSS 201012

Faraday rotation estimate over PALSAR L-band data

Full polarimetric dataOver bare surfaces μ>0.2

Compact polarimetric data

Thanks to the ASF for providing the data.

4

4

4

IGARSS 201013

Conclusion

• π/2 mode is required for low frequency spaceborne radar• Introduction of a parameter : the conformity coefficient

• Is FR-independent• Allows to distinguish 3 types of scattering

• Estimation of FR over bare surfaces identified by the conformity coefficient

Now FR is corrected

Can we use this type of data ?• Let’s see PolSAR applications

• 1) soil moisture estimate

IGARSS 201014

FP vs CP signatures

VV

HH

RV

RH

jS

S

S

S~

~

SHV ~ 0 over bare soil surfacesσ H

h (d

B)

σRh (dB)

10

10-30

-30 10

10

σ Vv (d

B)

σRv (dB)

Window size : 7x7 σHh/ σRh

σVv/ σRv

Stdv: <2dB

RH HH HV

HV VVRV

S S jS

S jSS

IGARSS 201015

FP vs CP soil moisture – Dubois et al. algorithm

FP soil moisture0 100%

100%

CP

soi

l moi

stur

e

Stdv : 4%

CP/FP soil moisture Estimated soil moisture CP & FP vs ground truth

Stdv : 2%

RAMSES L-band data, Le Moulin du Fâ, France

AIRSAR/WASHITA L-band data over Chickasha area

P. C. Dubois, J. van Zyl et T. Engman, Measuring Soil Moisture with Imaging Radars, IEEE Transactions on Geoscience and Remote Sensing, vol. 33, no. 4, pp. 915-926, Juillet 1995.

IGARSS 201016

Conclusion

• π/2 mode is required for low frequency spaceborne radar• Introduction of a parameter : the conformity coefficient

• Is FR-independent• Allows to distinguish 3 types of scattering

• Estimation of FR over bare surfaces identified by the conformity coefficient

• Compact PolSAR applications:• Estimate of soil moisture is possible over bare surfaces selected by μ

and using Dubois et al. Algorithm – RMS error of 2% over AIRSAR L-band data

Can we use this type of data ?• Let’s see PolSAR applications

• 1) soil moisture estimate• 2) biomass estimate (FP, FP reconstructed from CP and CP)

IGARSS 201017

Backscattering coefficients vs measured biomass – RAMSES P-band data over Nezer forest

(HV)

(RR) (RH)

IGARSS 201018

Biomass estimate vs in situ measurements – Nezer forest

RMS error=6.25 tons/ha

RMS error=6.63 tons/ha RMS error=12.2 tons/ha

RMS error=5.8 tons/ha

IGARSS 201019

Biomass map – Nezer forest

HVeBHV1274,08,205

'1465,0' 01,178 HVeBHV

RReBRR1626,0142,53Measured biomass

0 120 tons/ha

IGARSS 201020

ROI biomass map – Nezer forest

Measured biomass BHV BHV’BRR

IGARSS 201021

Conclusion

• π/2 mode is required for low frequency spaceborne radar• Introduction of a parameter : the conformity coefficient

• Is FR-independent• Allows to distinguish 3 types of scattering

• Estimation of FR over bare surfaces identified by the conformity coefficient

• Compact PolSAR applications:• Estimate of soil moisture is possible over bare surfaces selected by μ and

using Dubois et al. Algorithm – RMS error of 2% over AIRSAR L-band data• Quantify biomass with HV’ (RMS error : 6,25 tons/ha) and RR (6,63 tons/ha)

instead of HV (5,8 tons/ha)

• Add interferometry concept compact-PolInSAR potentials

IGARSS 201022

Compact-PolInSAR vs full-PolInSAR

• Compact-PolInSAR (C-PolInSAR) information is represented by a 4x4 matrix

• Full-PolInSAR (F-PolInSAR) information is represented by a 6x6 matrix

IGARSS 201023

PolInSAR applications – vegetation height estimate

• Flynn et al. algorithm

max j

we

Tww

wewe

T

jTj

*12

*

22211 TT

T

* *12 12

** *11 22

( )T T

TT T

w w w ww w

w Tww T w w T w

11 126 *

12 22T

TC

T

T. Flynn, M. Tabb et R. Carande, Estimation of Coherence Region Shapes in Polarimetric SAR Interferometry, AIRSAR Workshop, Mars 2002.

IGARSS 201024

Phase centers height (FP & CP)

Phase centers height FP

Phase centers height CP

Nezer forest, P-band

IGARSS 201025

Vegetation height – Nezer forest P-band

S.R. Cloude and K.P. Papathanassiou, A 3-Stage Inversion Process for Polarimetric SAR Interferometry, IEE Proceedings Radar, Sonar & Navigation, vol. 150, no. 3, June 2003.

RMS : 1m, Bias : 0,4m (FP)

RMS : 1,1m, Bias : 0,4m (CP)

RMS : 2,45m, Bias : -1,8m (FP)

RMS : 2,5m, Bias : -1,78m (CP)

IGARSS 201026

Conclusion

• π/2 mode is required for low frequency spaceborne radar• Introduction of a parameter : the conformity coefficient

• Is FR-independent• Allows to distinguish 3 types of scattering

• Estimation of FR over bare surfaces identified by the conformity coefficient

• Compact PolSAR applications:• Estimate of soil moisture is possible over bare surfaces selected by μ and

using Dubois et al. Algorithm – RMS error of 2% over AIRSAR L-band data• Quantify biomass with HV’ (RMS error : 6,25 tons/ha) and RR (6,63 tons/ha)

instead of HV (5,8 tons/ha)

• Compact PolInSAR applications:• C-PolInSAR coherence region < F-PolInSAR coherence region• C-PolInSAR coherence region F-PolInSAR coherence region

• System implications Calibration

IGARSS 201027

Calibration of a CP system

• CP system:

• System has to be perfect before transmission because it is not possible to correct afterwards

• With a perfect transmission 4 unknowns δ1, δ2, Ω, f1

1, j

R TM A r e D R SR D Nj

1, j

RM A r e D R SR Nj

1 1

j j

2

23

1

21

2

f

fj

α ~ 1

β ~ -jδf 2~1

2 3

1 1 4 2

1 1cos sin cos sin 11,

sin cos sin cos2RH HH HV Hj

RV VH VV V

M S S NA r e

M S S Nf f j

IGARSS 201028

• Dihedral at 0°

• Dihedral at 45°

• Expansion of

• Trihedral at 0°

Calibration of a CP system

12

1

1212

11

cossinsincos

cossinsincos

2

1

fjS

jSAe

fjSfS

jSSeAeM

HV

HVj

VVHH

VVHHjj

0

0

0

0

D

D

AS

A

0

01

2 1

1DRH

DRV

M j

jfM

0

0

D

D

AS

A

1

1 2

DRHDRV

M j

M f j

0

01

1

2

DDRVRH

D DRV RH

MMm

M M

0

0

*

1 12

D DRV RV

DDRHRH

M Mje

MM

0 0

0 0

*

1 2

D D DDRV RV RVRH

D DD DRH RVRH RH

M M MMj

M MM M

D DRH RVM M

2* * *2 1 1 1 1

DRHDRV

Mf f jf

M

0

0

T

T

AS

A

1

2T DRH RHT DRV RV

jf

M MM M

*

*

2 *2 1 1 1 1

DRH

DRV

Mf f jf

M

0

0

1

ln 22

D DD TRV RVRH

T D DDRH RHRH

M MMj Aj j

M A MM

IGARSS 201029

Conclusion

• π/2 mode is required for low frequency spaceborne radar• Introduction of a parameter : the conformity coefficient

• Is FR-independent• Allows to distinguish 3 types of scattering

• Estimation of FR over bare surfaces identified by the conformity coefficient

• Compact PolSAR applications:• Estimate of soil moisture is possible over bare surfaces selected by μ and

using Dubois et al. Algorithm – RMS error of 2% over AIRSAR L-band data• Quantify biomass with HV’ (RMS error : 6,25 tons/ha) and RR (6,63 tons/ha)

instead of HV (5,8 tons/ha)• Compact PolInSAR applications:

• C-PolInSAR coherence region < F-PolInSAR coherence region• C-PolInSAR coherence region F-PolInSAR coherence region

• Calibration• Require a perfect transmission• Suggest 3 external targets to calibrate a CP system