SlideShare a Scribd company logo
•Remote
  Remote Sensing Laboratory   •Sensing
  Universitat Politècnica de Catalunya
                              •Laboratory




    Phase error assessment of
MIRAS/SMOS by means of Redundant
        Space Calibration

Rubén Dávila(1), Francesc Torres(1), Nuria Duffo(1), Ignasi
 Corbella(1), Miriam Pablos(1) and Manuel Martín-Neira (2)

(1) Remote Sensing Laboratory. Universitat Politècnica de Catalunya,
    Barcelona.SMOS Barcelona Expert Centre
(2) European Space Agency (ESA-ESTEC). Noordwijk. The Netherlands




                                                                  1/20
•Remote
            Remote Sensing Laboratory   •Sensing
            Universitat Politècnica de Catalunya
                                        •Laboratory

     The Soil Moisture & Ocean Salinity Earth Explorer Mission (ESA)
                                                                      Aperture Synthesis
                                                                  Interferometric Radiometer
                                                               • MIRAS instrument concept
                                                                     - Y-shaped array (arm length ~ 4.5 m)
                                                                     - 21 dual-pol. L-band antennas / arm
                                                                     - spacing 0.875 λ (~1400 MHz)
                                                                     -no scanning mechanisms,
                                                                            2D imaging by Fourier synthesis
                                                                     -(u,v) antenna separation in wavelengths

                                                              2D images formed by Fourier Synthesis
                                                             (ideal case). Cross correlation of the signals
                                                             collected by each antenna pair gives the so-
                                                             called: Visibility samples V(u,v):

   Launched November 2009
                                                                                        TB (ξ, η) − Tph        2
                                                                                                                  
                                                           V(u, v) =< b1 (t)b (t) >= F 
                                                                             *
                                                                             2                           F(ξ, η) 
(SMOS artist’s view, by EADS-CASA Space Division, Spain)
                                                                                        1−ξ −η
                                                                                       
                                                                                                 2    2
                                                                                                                  
                                                                                                                  
                                                      IGARSS 2011 Vancouver                                    2
•Remote
      Remote Sensing Laboratory   •Sensing
      Universitat Politècnica de Catalunya
                                  •Laboratory


 Simplified block diagram of a single baseline
                                                                      MIRAS measures
                                                                   normalized correlations:


                               antenna 1

                                                                                             Mkj
                                antenna 2



                                                 antenna planes

                                          System temperatures measured by a power detector in each receiver




Visibility sample at A                           TsysAk TsysAj
                    V = M kj
the antenna plane kj                                        jφkj
                                                               A
                                                                      Fringe Wash function at the origin (τ=0):
                                                Gkj (0) e              • Modulus (≈1)
                                           IGARSS 2011 Vancouver       • FWF Phase at antenna plane       3
•Remote
      Remote Sensing Laboratory   •Sensing
      Universitat Politècnica de Catalunya
                                  •Laboratory


                              Framework of the activity
SMOS is producing images within expected performance. However, there is
some degree of image distortion (spatial errors) due to a number of causes.

This research activity is devoted to assess the different contributions of
spatial errors, with two objectives in mind:
         • SMOS Improved performance
         • SMOS follow-on specifications

The RSC method is devoted to assess the peformance of phase calibration.

For calibration purposes, the phase calibration term (antenna plane) is modeled as:



                  φkj = (φkant − φ jant ) + (φkrec − φ jrec ) + φkj
                    A                                            FWF




             Antenna phase terms                Receiver phases    Fringe-wash term

                                           IGARSS 2011 Vancouver                      4
•Remote
        Remote Sensing Laboratory   •Sensing
        Universitat Politècnica de Catalunya
                                    •Laboratory



                            SMOS phase calibration strategy

             • Receiver phase drift is calibrated by periodic (2-10 min) correlated noise
               injection (LO phase track)

             • Antenna phase term (manufacturing tolerances): Measured on ground

             • Fringe washing term due to filter response differences (negligible)
Antenna                     Receiver
 plane             φkant     plane       φkrec                    Antenna phase test set-up


                   A L                           receiver " k "
         η
                   C                                     M kj
 Noise injection
                                       Correlator
                   Switch


Front end phase model                            receiver " j "

                                                     IGARSS 2011 Vancouver                    5
•Remote
       Remote Sensing Laboratory   •Sensing
       Universitat Politècnica de Catalunya
                                   •Laboratory


                        Redundant Space Calibration (RSC)
Redundant baselines measure the same visibility using a different pair of antennas




                                                                        Redundant baselines




    Visibility phase measured by a baseline:           φVkj = φk − φj + φscene,kj
   RSC phase differences are independent of the phase of the scene

     Baseline phase differences:            φVkj − φVji =k − 2φj + φi
                                                         φ
                                            IGARSS 2011 Vancouver                             6
•Remote
          Remote Sensing Laboratory   •Sensing
          Universitat Politècnica de Catalunya
                                      •Laboratory



                                   RSC system of equations
     A system of equations can be built using independent RSC equations


0    0     1     −2     1     0    … …         0   
                                                   
0    0 0 1 −2 1 0 … 0                                                                 Applied on calibrated
…    … … … … … … … …                                                                  visibilities the RSC
                                                                                      method retrieves the
0    … … … … 0                     1    −2 1       ·φreceivers = φphase differences
…                                                                                     residual phase error
      … −1 1 … −1                   1    .. …
                                                   
…    −1 … 1 … …                    1    −1 …       
…    … … … … … … … …                               
                                                   
     A matrix: 66 x 69                                             Underdetermined system
     Receivers vector: 69 x 1                                  (three unknown phases, rank = 66)
     Phase differences vector: 66 x 1
                                                              Moore-Penrose pseudoinverse matrix
      66 equations, 69 unknowns

      Averaging is required to reduce uncertainty due to thermal noise
                                               IGARSS 2011 Vancouver                                       7
•Remote
       Remote Sensing Laboratory   •Sensing
       Universitat Politècnica de Catalunya
                                   •Laboratory



   Averaging: visibility measurements must be carefully selected
   • Low visibility amplitude: produces unwanted variations and jumps
   • Fast scene changes: phase bias in land-ocean transitions
   • RFI: interferences that spoils the phase values

                                                        Land-ocean transition




Low visibility
  amplitude




                                                                                RFI



                                            IGARSS 2011 Vancouver                     8
•Remote
Remote Sensing Laboratory   •Sensing
Universitat Politècnica de Catalunya
                            •Laboratory



      RSC: examples of good quality visibility samples



             Averaging
               area                            Averaging
                                                 area
                                                                         Averaging
                                                                           area


      Arm A                               Arm B                     Arm C




                                                     Red line: Average snap-shots




                                     IGARSS 2011 Vancouver                          9
•Remote
    Remote Sensing Laboratory   •Sensing
    Universitat Politècnica de Catalunya
                                •Laboratory



                       RSC: Impact of undetermination
The 3 unknown phases have a physical meaning:




                    Tilt angle
                                                                 Steering angle




                                                                    Pointing error


   Common path delay                             Irrelevant
                                         IGARSS 2011 Vancouver                       10
•Remote
   Remote Sensing Laboratory   •Sensing
   Universitat Politècnica de Catalunya
                               •Laboratory



             RSC: Pointing error in the phase retrievals
Simulations show that a pointing error yields a linear phase error directly
related to the antenna position in the arms.


                                                           φerror,bslN = a·u bslN + b·v bslN


                                                                                        a      b 
                                                    TBcalibrated (ξ, η) = TBideal  ξ −    ,η−    
                                                                                       2π     2π 
                                                                                  a
                                                                    ξps ' = ξps −
                                                                                 2π
                                                                                  b
                                                                    ηps ' = ps −
                                                                           η
                                                                                 2π

     Retrieval error linear in each arm
 The pointing error can be corrected, if required, using a point source (e.g, an
 interference at a known position ξps , ηps)

                                        IGARSS 2011 Vancouver                                    11
•Remote
    Remote Sensing Laboratory   •Sensing
    Universitat Politècnica de Catalunya
                                •Laboratory



       Assessment on the pointing error in RSC retrievals
Simulation: SMOS point source retrieval by the RSC method: random phase error




         Ideal                           Phase corrupted         Corrected

    •Image blurring (example, σphases = 25º)
    • Secondary lobes increase
    • Small pointing error: the maximum has been displaced.
 Once the point source is RSC calibrated, image blurring and secondary lobes are
corrected. However, the pointing error is not compensated.
                                                                                   12
                                         IGARSS 2011 Vancouver
•Remote
   Remote Sensing Laboratory   •Sensing
   Universitat Politècnica de Catalunya
                               •Laboratory



              RSC implementation (i): Good/bad estimations
Due to pointing error, the difference between two phase retrievals must be
linear. This property is used to discard bad estimations of the RSC phases
           φretrieved = φIVT,error + φpoint ing error
            1                         1


           φretrieved = φIVT,error + φpoint ing error
             2                        2


   φretrieved − φretrieved = φpoint ing error − φpoint ing error
     2           1            2                  1
                                                                                     Linear




                  Bad estimations                                           Good estimations
                                                    IGARSS 2011 Vancouver                      13
•Remote
       Remote Sensing Laboratory   •Sensing
       Universitat Politècnica de Catalunya
                                   •Laboratory



                                   RSC retrieved phases
Final RSC phases retrieved by averaging RSC phases from 38 orbits over the ocean

          Horizontal Phases                      Vertical Phases
                                                                      RSC Phase Error
                                                                        dispersion

                                                                        σH =5.97º
                                                                        σV =3.17º

                                                                    • RSC gives a conservative
     Horizontal Mean Phases                  Vertical Mean Phases
                                                                     upper bound for SMOS

                                                                     residual phase errors

                                                                    • RSC phase dispersion very

                                                                     much contributed by

                                                                     pointing error


                                            IGARSS 2011 Vancouver                          14
•Remote
      Remote Sensing Laboratory   •Sensing
      Universitat Politècnica de Catalunya
                                  •Laboratory



                 RSC: phase error impact of pointing error
                                                                   Mean pointing error (H)

                                                              Horizontal Phases
                                                                 Simulation

                         r
                                                              SMOS std




                                                   <r>
                                                               Horizontal Std
                                                                        σphases (°)
Simulation: point source shift for 200 cases
with σph=20º. 95% of points within a radius              σH =5.97º               σV =3.17º
r=2mrayleigh centred at the point source real
position
                                                         rH = 0.00066           rV = 0.00037
                                                    ∆L H = km
                                                         0.76                  ∆L V = km
                                                                                    0.43

             ΔLH and ΔLV below 2% of SMOS resolution (42 km)
                                           IGARSS 2011 Vancouver                               15
•Remote
Remote Sensing Laboratory   •Sensing
Universitat Politècnica de Catalunya
                            •Laboratory



RSC peformance assesssment: RFI in the Caribbean Sea
           Interference from a vessel (11/02/2010, 21:23 semi-orbit)




                                   IGARSS 2011 Vancouver

                                                                       16
•Remote
Remote Sensing Laboratory   •Sensing
Universitat Politècnica de Catalunya
                            •Laboratory



RSC peformance assesssment: RFI in the Caribbean Sea
                                          Horizontal




                                IGARSS 2011 Vancouver

                                                        17
•Remote
Remote Sensing Laboratory   •Sensing
Universitat Politècnica de Catalunya
                            •Laboratory



 RSC peformance assessment: RFI in the Caribbean Sea

– Primary to Secondary Lobe Ratio (H):
                        Case              Primary to Secondary Lobe Ratio
                 Real Point Source                   17,40 dB
             Corrected Point Source                  16,50 dB

– Primary to Secondary Lobe Ratio (V):
                        Case              Primary to Secondary Lobe Ratio
                Real Point Source                    17,40 dB
             Corrected Point Source                  16,65 dB

– The uncorrected RFI presents a main-to-secondary lobe ratio very
  close to an ideal point source.
– The RSC method uncertainty above SMOS phase error accuracy!!


                                                                            18
•Remote
Remote Sensing Laboratory   •Sensing
Universitat Politècnica de Catalunya
                            •Laboratory



   RSC implementation: Interference in Cáceres (Spain)
                                          Vertical




                                                         19
•Remote
    Remote Sensing Laboratory   •Sensing
    Universitat Politècnica de Catalunya
                                •Laboratory



                                        Conclusions
• The RSC method cannot be used to phase calibrate SMOS in a per snap
shot basis due to the need for long averaging and filtering

• SMOS orbital phase drift requires periodic (2-10 min) correlated noise
injection (LO phase track)


• The RSC is used to validate the consistency of SMOS phase calibrated
visibilities:

    •RSC phase retrieval accuracy limited by undetermination (pointing
    error)
    •SMOS phase errors well below σH=5.97 º and σV=3.17º, probably very
    close to the σ =1º target

•Assessment on point sources (RFI) shows that the impact of SMOS
residual phase errors on image distortion is probably negligible
                                         IGARSS 2011 Vancouver        20

More Related Content

PDF
IGARSS11 End-to-end calibration v2.pdf
PDF
Opera neuvel
PDF
Opera neuvel de-cern
PDF
Bava_ Inrim
PDF
Tuning the transport properties of graphene through ac fields
PDF
Poster workshop Bad Honnef Germany 2011
PDF
WE4.L09 - ORTHOGONAL POLARIMETRIC SAR PROCESSOR BASED ON SIGNAL AND INTERFERE...
PDF
Meroli Grazing Angle Techinique Pixel2010
IGARSS11 End-to-end calibration v2.pdf
Opera neuvel
Opera neuvel de-cern
Bava_ Inrim
Tuning the transport properties of graphene through ac fields
Poster workshop Bad Honnef Germany 2011
WE4.L09 - ORTHOGONAL POLARIMETRIC SAR PROCESSOR BASED ON SIGNAL AND INTERFERE...
Meroli Grazing Angle Techinique Pixel2010

What's hot (12)

PDF
3MPL Graduate School Days
PDF
R-matrix calculations for electron impact excitation and modelling applicatio...
PDF
PANIC2011_Final
PPT
Microwave Filter
PDF
Fairness of the WiMAX System
PDF
Dielectronic recombination and stability of warm gas in AGN
PPTX
Determination of 2D shallow S wave velocity profile using waveform inversion ...
PPTX
Quantum storage and manipulation of heralded single photons in atomic quantum...
PDF
Oltre l'orizzonte cosmologico
PPTX
Ee600 lab3 hal9000_grp
PDF
Evidence Of Bimodal Crystallite Size Distribution In Microcrystalline Silico...
3MPL Graduate School Days
R-matrix calculations for electron impact excitation and modelling applicatio...
PANIC2011_Final
Microwave Filter
Fairness of the WiMAX System
Dielectronic recombination and stability of warm gas in AGN
Determination of 2D shallow S wave velocity profile using waveform inversion ...
Quantum storage and manipulation of heralded single photons in atomic quantum...
Oltre l'orizzonte cosmologico
Ee600 lab3 hal9000_grp
Evidence Of Bimodal Crystallite Size Distribution In Microcrystalline Silico...
Ad

Viewers also liked (7)

PDF
expodesarrollo29
KEY
Iso9001 Agile Teams
PDF
International succes med cloud og agile
PDF
ntrs_investor_day_cfo
PDF
Final Alfresco Active Endpoints Tech Talk Live June 12 2009
PPTX
Styr gennem kaos
PDF
Bf25342345
expodesarrollo29
Iso9001 Agile Teams
International succes med cloud og agile
ntrs_investor_day_cfo
Final Alfresco Active Endpoints Tech Talk Live June 12 2009
Styr gennem kaos
Bf25342345
Ad

Similar to Phase error assessment of MIRASSMOS by means of Redundant Space Calibration.pdf (20)

PPT
igarss11_1126_corbella.ppt
PPT
MIRAS: the instrument aboard SMOS
PPT
MIRAS: The SMOS Instrument
PPT
Principle of FMCW radar
PDF
Miller - Remote Sensing and Imaging Physics - Spring Review 2012
PDF
IGARSS_PolInSAR_TDX.pdf
PPT
GAS@IGARSS2011.ppt
PDF
FR2_T04_1_PAU_INTA_MicroSat_A_Camps.pdf
PDF
WE3.L10.3: THE FUTURE OF SPACEBORNE SYNTHETIC APERTURE RADAR
PDF
TU2.L09.1 - COMPACT POLARIMETRY AT THE MOON: THE MINI-RF RADARS
PDF
TU2.L09.1 - COMPACT POLARIMETRY AT THE MOON: THE MINI-RF RADARS
PDF
3MPL Graduate School Days presentation
PDF
Within the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdf
PDF
SMOS UPC- Barcelona Activa
PDF
INITIAL OBSERVATION RESULTS FOR PRECIPITATION ON THE KU-BAND BROADBAND RADAR ...
PDF
Freznal zone
PDF
March 11th Japan Earthquake and Tsunami, Beyond the Frontiers: What we observ...
PPT
Advances in polarimetric X-band weather radar
PDF
IGARSS__RTC.pdf
PDF
Nonlinear Range Cell Migration (RCM) Compensation Method for SpaceborneAirbor...
igarss11_1126_corbella.ppt
MIRAS: the instrument aboard SMOS
MIRAS: The SMOS Instrument
Principle of FMCW radar
Miller - Remote Sensing and Imaging Physics - Spring Review 2012
IGARSS_PolInSAR_TDX.pdf
GAS@IGARSS2011.ppt
FR2_T04_1_PAU_INTA_MicroSat_A_Camps.pdf
WE3.L10.3: THE FUTURE OF SPACEBORNE SYNTHETIC APERTURE RADAR
TU2.L09.1 - COMPACT POLARIMETRY AT THE MOON: THE MINI-RF RADARS
TU2.L09.1 - COMPACT POLARIMETRY AT THE MOON: THE MINI-RF RADARS
3MPL Graduate School Days presentation
Within the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdf
SMOS UPC- Barcelona Activa
INITIAL OBSERVATION RESULTS FOR PRECIPITATION ON THE KU-BAND BROADBAND RADAR ...
Freznal zone
March 11th Japan Earthquake and Tsunami, Beyond the Frontiers: What we observ...
Advances in polarimetric X-band weather radar
IGARSS__RTC.pdf
Nonlinear Range Cell Migration (RCM) Compensation Method for SpaceborneAirbor...

More from grssieee (20)

PDF
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
PDF
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
PPTX
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
PPT
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
PPTX
GMES SPACE COMPONENT:PROGRAMMATIC STATUS
PPTX
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
PPT
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
PPT
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
PPT
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
PPT
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
PDF
Test
PPT
test 34mb wo animations
PPT
Test 70MB
PPT
Test 70MB
PDF
2011_Fox_Tax_Worksheets.pdf
PPT
DLR open house
PPT
DLR open house
PPT
DLR open house
PPT
Tana_IGARSS2011.ppt
PPT
Solaro_IGARSS_2011.ppt
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
GMES SPACE COMPONENT:PROGRAMMATIC STATUS
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
Test
test 34mb wo animations
Test 70MB
Test 70MB
2011_Fox_Tax_Worksheets.pdf
DLR open house
DLR open house
DLR open house
Tana_IGARSS2011.ppt
Solaro_IGARSS_2011.ppt

Recently uploaded (20)

PPTX
VMware vSphere Foundation How to Sell Presentation-Ver1.4-2-14-2024.pptx
PDF
Per capita expenditure prediction using model stacking based on satellite ima...
PDF
NewMind AI Monthly Chronicles - July 2025
PDF
Unlocking AI with Model Context Protocol (MCP)
PDF
CIFDAQ's Market Insight: SEC Turns Pro Crypto
PDF
Reach Out and Touch Someone: Haptics and Empathic Computing
PDF
Shreyas Phanse Resume: Experienced Backend Engineer | Java • Spring Boot • Ka...
PDF
Network Security Unit 5.pdf for BCA BBA.
PDF
Agricultural_Statistics_at_a_Glance_2022_0.pdf
PPTX
Understanding_Digital_Forensics_Presentation.pptx
PPTX
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
PDF
TokAI - TikTok AI Agent : The First AI Application That Analyzes 10,000+ Vira...
PDF
Building Integrated photovoltaic BIPV_UPV.pdf
PPT
“AI and Expert System Decision Support & Business Intelligence Systems”
PPTX
Digital-Transformation-Roadmap-for-Companies.pptx
PPTX
KOM of Painting work and Equipment Insulation REV00 update 25-dec.pptx
PDF
Advanced methodologies resolving dimensionality complications for autism neur...
PDF
Modernizing your data center with Dell and AMD
PDF
Encapsulation theory and applications.pdf
PDF
Review of recent advances in non-invasive hemoglobin estimation
VMware vSphere Foundation How to Sell Presentation-Ver1.4-2-14-2024.pptx
Per capita expenditure prediction using model stacking based on satellite ima...
NewMind AI Monthly Chronicles - July 2025
Unlocking AI with Model Context Protocol (MCP)
CIFDAQ's Market Insight: SEC Turns Pro Crypto
Reach Out and Touch Someone: Haptics and Empathic Computing
Shreyas Phanse Resume: Experienced Backend Engineer | Java • Spring Boot • Ka...
Network Security Unit 5.pdf for BCA BBA.
Agricultural_Statistics_at_a_Glance_2022_0.pdf
Understanding_Digital_Forensics_Presentation.pptx
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
TokAI - TikTok AI Agent : The First AI Application That Analyzes 10,000+ Vira...
Building Integrated photovoltaic BIPV_UPV.pdf
“AI and Expert System Decision Support & Business Intelligence Systems”
Digital-Transformation-Roadmap-for-Companies.pptx
KOM of Painting work and Equipment Insulation REV00 update 25-dec.pptx
Advanced methodologies resolving dimensionality complications for autism neur...
Modernizing your data center with Dell and AMD
Encapsulation theory and applications.pdf
Review of recent advances in non-invasive hemoglobin estimation

Phase error assessment of MIRASSMOS by means of Redundant Space Calibration.pdf

  • 1. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory Phase error assessment of MIRAS/SMOS by means of Redundant Space Calibration Rubén Dávila(1), Francesc Torres(1), Nuria Duffo(1), Ignasi Corbella(1), Miriam Pablos(1) and Manuel Martín-Neira (2) (1) Remote Sensing Laboratory. Universitat Politècnica de Catalunya, Barcelona.SMOS Barcelona Expert Centre (2) European Space Agency (ESA-ESTEC). Noordwijk. The Netherlands 1/20
  • 2. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory The Soil Moisture & Ocean Salinity Earth Explorer Mission (ESA) Aperture Synthesis Interferometric Radiometer • MIRAS instrument concept - Y-shaped array (arm length ~ 4.5 m) - 21 dual-pol. L-band antennas / arm - spacing 0.875 λ (~1400 MHz) -no scanning mechanisms, 2D imaging by Fourier synthesis -(u,v) antenna separation in wavelengths 2D images formed by Fourier Synthesis (ideal case). Cross correlation of the signals collected by each antenna pair gives the so- called: Visibility samples V(u,v): Launched November 2009  TB (ξ, η) − Tph 2  V(u, v) =< b1 (t)b (t) >= F  * 2 F(ξ, η)  (SMOS artist’s view, by EADS-CASA Space Division, Spain)  1−ξ −η  2 2   IGARSS 2011 Vancouver 2
  • 3. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory Simplified block diagram of a single baseline MIRAS measures normalized correlations: antenna 1 Mkj antenna 2 antenna planes System temperatures measured by a power detector in each receiver Visibility sample at A TsysAk TsysAj V = M kj the antenna plane kj jφkj A Fringe Wash function at the origin (τ=0): Gkj (0) e • Modulus (≈1) IGARSS 2011 Vancouver • FWF Phase at antenna plane 3
  • 4. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory Framework of the activity SMOS is producing images within expected performance. However, there is some degree of image distortion (spatial errors) due to a number of causes. This research activity is devoted to assess the different contributions of spatial errors, with two objectives in mind: • SMOS Improved performance • SMOS follow-on specifications The RSC method is devoted to assess the peformance of phase calibration. For calibration purposes, the phase calibration term (antenna plane) is modeled as: φkj = (φkant − φ jant ) + (φkrec − φ jrec ) + φkj A FWF Antenna phase terms Receiver phases Fringe-wash term IGARSS 2011 Vancouver 4
  • 5. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory SMOS phase calibration strategy • Receiver phase drift is calibrated by periodic (2-10 min) correlated noise injection (LO phase track) • Antenna phase term (manufacturing tolerances): Measured on ground • Fringe washing term due to filter response differences (negligible) Antenna Receiver plane φkant plane φkrec Antenna phase test set-up A L receiver " k " η C M kj Noise injection Correlator Switch Front end phase model receiver " j " IGARSS 2011 Vancouver 5
  • 6. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory Redundant Space Calibration (RSC) Redundant baselines measure the same visibility using a different pair of antennas Redundant baselines Visibility phase measured by a baseline: φVkj = φk − φj + φscene,kj RSC phase differences are independent of the phase of the scene Baseline phase differences: φVkj − φVji =k − 2φj + φi φ IGARSS 2011 Vancouver 6
  • 7. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC system of equations A system of equations can be built using independent RSC equations 0 0 1 −2 1 0 … … 0    0 0 0 1 −2 1 0 … 0  Applied on calibrated … … … … … … … … …  visibilities the RSC   method retrieves the 0 … … … … 0 1 −2 1 ·φreceivers = φphase differences …  residual phase error … −1 1 … −1 1 .. …   … −1 … 1 … … 1 −1 …  … … … … … … … … …    A matrix: 66 x 69 Underdetermined system Receivers vector: 69 x 1 (three unknown phases, rank = 66) Phase differences vector: 66 x 1 Moore-Penrose pseudoinverse matrix 66 equations, 69 unknowns Averaging is required to reduce uncertainty due to thermal noise IGARSS 2011 Vancouver 7
  • 8. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory Averaging: visibility measurements must be carefully selected • Low visibility amplitude: produces unwanted variations and jumps • Fast scene changes: phase bias in land-ocean transitions • RFI: interferences that spoils the phase values Land-ocean transition Low visibility amplitude RFI IGARSS 2011 Vancouver 8
  • 9. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC: examples of good quality visibility samples Averaging area Averaging area Averaging area Arm A Arm B Arm C Red line: Average snap-shots IGARSS 2011 Vancouver 9
  • 10. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC: Impact of undetermination The 3 unknown phases have a physical meaning: Tilt angle Steering angle Pointing error Common path delay Irrelevant IGARSS 2011 Vancouver 10
  • 11. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC: Pointing error in the phase retrievals Simulations show that a pointing error yields a linear phase error directly related to the antenna position in the arms. φerror,bslN = a·u bslN + b·v bslN  a b  TBcalibrated (ξ, η) = TBideal  ξ − ,η−   2π 2π  a ξps ' = ξps − 2π b ηps ' = ps − η 2π Retrieval error linear in each arm The pointing error can be corrected, if required, using a point source (e.g, an interference at a known position ξps , ηps) IGARSS 2011 Vancouver 11
  • 12. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory Assessment on the pointing error in RSC retrievals Simulation: SMOS point source retrieval by the RSC method: random phase error Ideal Phase corrupted Corrected •Image blurring (example, σphases = 25º) • Secondary lobes increase • Small pointing error: the maximum has been displaced. Once the point source is RSC calibrated, image blurring and secondary lobes are corrected. However, the pointing error is not compensated. 12 IGARSS 2011 Vancouver
  • 13. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC implementation (i): Good/bad estimations Due to pointing error, the difference between two phase retrievals must be linear. This property is used to discard bad estimations of the RSC phases φretrieved = φIVT,error + φpoint ing error 1 1 φretrieved = φIVT,error + φpoint ing error 2 2 φretrieved − φretrieved = φpoint ing error − φpoint ing error 2 1 2 1 Linear Bad estimations Good estimations IGARSS 2011 Vancouver 13
  • 14. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC retrieved phases Final RSC phases retrieved by averaging RSC phases from 38 orbits over the ocean Horizontal Phases Vertical Phases RSC Phase Error dispersion σH =5.97º σV =3.17º • RSC gives a conservative Horizontal Mean Phases Vertical Mean Phases upper bound for SMOS residual phase errors • RSC phase dispersion very much contributed by pointing error IGARSS 2011 Vancouver 14
  • 15. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC: phase error impact of pointing error Mean pointing error (H) Horizontal Phases Simulation r SMOS std <r> Horizontal Std σphases (°) Simulation: point source shift for 200 cases with σph=20º. 95% of points within a radius σH =5.97º σV =3.17º r=2mrayleigh centred at the point source real position rH = 0.00066 rV = 0.00037 ∆L H = km 0.76 ∆L V = km 0.43 ΔLH and ΔLV below 2% of SMOS resolution (42 km) IGARSS 2011 Vancouver 15
  • 16. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC peformance assesssment: RFI in the Caribbean Sea Interference from a vessel (11/02/2010, 21:23 semi-orbit) IGARSS 2011 Vancouver 16
  • 17. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC peformance assesssment: RFI in the Caribbean Sea Horizontal IGARSS 2011 Vancouver 17
  • 18. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC peformance assessment: RFI in the Caribbean Sea – Primary to Secondary Lobe Ratio (H): Case Primary to Secondary Lobe Ratio Real Point Source 17,40 dB Corrected Point Source 16,50 dB – Primary to Secondary Lobe Ratio (V): Case Primary to Secondary Lobe Ratio Real Point Source 17,40 dB Corrected Point Source 16,65 dB – The uncorrected RFI presents a main-to-secondary lobe ratio very close to an ideal point source. – The RSC method uncertainty above SMOS phase error accuracy!! 18
  • 19. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory RSC implementation: Interference in Cáceres (Spain) Vertical 19
  • 20. •Remote Remote Sensing Laboratory •Sensing Universitat Politècnica de Catalunya •Laboratory Conclusions • The RSC method cannot be used to phase calibrate SMOS in a per snap shot basis due to the need for long averaging and filtering • SMOS orbital phase drift requires periodic (2-10 min) correlated noise injection (LO phase track) • The RSC is used to validate the consistency of SMOS phase calibrated visibilities: •RSC phase retrieval accuracy limited by undetermination (pointing error) •SMOS phase errors well below σH=5.97 º and σV=3.17º, probably very close to the σ =1º target •Assessment on point sources (RFI) shows that the impact of SMOS residual phase errors on image distortion is probably negligible IGARSS 2011 Vancouver 20