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IGARSS11 End-to-end calibration v2.pdf
1. •Remote
•Sensing
•Laboratory
SMOS brightness temperature
measurement and end-to-end calibration
Francesc Torres(1), Ignasi Corbella(1), Nuria Duffo(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
IGARSS 2011 Vancouver 1/16
2. •Remote
•Sensing
•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, courtesy of EADS-CASA Space Division, Spain)
1−ξ −η
2 2
IGARSS 2011 Vancouver 2/16
3. •Remote
•Sensing
•Laboratory
Simplified block diagram of a single baseline
MIRAS measures
normalized correlations:
antenna 1
Mkj
antenna 2
antenna planes
Tsys measured by PMS
Visibility sample at the antenna plane (Power Measurement System)
TsysAk TsysAj System temperature
v A k − voff k
Tsys Ak =
V = M kj
A
kj
at antenna plane A
G PMSk
Gkj Fringe Wash function at the origin
3/16
IGARSS 2011 Vancouver
4. •Remote
•Sensing
•Laboratory
Interferometric radiometer calibration
IRad calibration
1. Relative calibration
(image distortion)
2. Absolute calibration
(Level)
Before applying the "black box" approach MIRAS raw measurements (voltages and
correlations) require a comprehensive error correction process
IGARSS 2011 Vancouver 4/16
5. •Remote
•Sensing
•Laboratory
SMOS calibration
SMOS calibration scheme can be described from different points of view
1. Calibration • Visibility amplitude, phase, offset
• Reference radiometer (absolute amplitude)
parameter • Antenna errors (image distortion)
2. Instrument • Internal: Correlated/uncorrelated noise injection
• External: Flat target transformation/Reference radiometer
configuration • Ground: Image Validation Tests/ Factory parameters
3. Calibration • Snap-shot: self-calibration
• Weekly: PMS offset (4 point cal)
periodicity • Monthly: Reference radiometer/U-offset/FWF parameters
• Yearly: Flat Target/thermal sensitivity/Heater parameters
• Stable: Ground tests
An interferometric radiometer requires a complex calibration scheme!!!
IGARSS 2011 Vancouver 5/16
7. •Remote
•Sensing
•Laboratory
IRad calibration rationale
The error model:
• Inherited from high accuracy network analyzer techniques
• Based on physical/electrical properties of the measured magnitude
• Applied at subsystem level (nested approach)
• Parameterization: the error model coefficients.
• Selection of the standards of calibration.
• E.g. a matched load, statistical properties, etc.
• Measurement of the error coefficients
• Error extraction (calibration)
• Assessment of residual errors after calibration
• Fine tuning of the error model if required
IGARSS 2011 Vancouver 7/16
8. •Remote
•Sensing
•Laboratory
The error model (i)
The combination of both hardware and software procedures turns a real
subsystem that produces corrupted raw measurements into an ideal block
easier to integrate complex normalized correlation scheme
Ideal in a higher level data flow
IDEAL CORRELATOR
Ik I/Q sampling with 1 Bit / 2 Level
1100101… Ik I j (normalized)
SELF-CALIBRATION
0101101…
Qk Digital correlation r i
= M kj + jM kj
correlators
M kj
-Sampling offset
-Quadrature error
Ij
1100111… -Non -linearity
Complex, zero offset,
quadrature corrected,
Qj normalized correlation
0111100… Qk I j
(snap-shot)
IGARSS 2011 Vancouver 8/16
9. •Remote
•Sensing
•Laboratory
The error model (ii)
Residual error assessment and iterative fine tuning of the error model has
been a key approach to improve subsystem performance
Example: digital correlator offset
With 1-0 correction With 1-0 and truncation error correction
0.6 0.6
Mean= -0.21-0.22i cu
0.4 0.4
σ=0.03cu
Mean= -0.00061+0.00029i cu
0.2 σ=0.029cu
0.2
ℑ m[M] (cu)
ℑ m[M] (cu)
0 0
-0.2 -0.2
-0.4 -0.4
avg~1min avg ~12h avg ~12h
-0.4 -0.2 0 0.2 0.4 0.6 -0.4 -0.2 0 0.2 0.4 0.6
ℜ e[M] (cu) ℜ e[M] (cu)
m≈10-3 m≈2·10-5 MIRAS:
m≈6·10-8
AMIRAS: MIRAS:
σ ≈10-4 σ ≈3·10-6 σ ≈3·10-6
IGARSS 2011 Vancouver 9/16
10. •Remote
•Sensing
•Laboratory
The error model (iii)
Correlation denormalization: a PMS placed at each LICEF measures System
Temperature and correlation loss
IDEAL DETECTOR
Linear, zero offset,
temperature corrected,
power detector
(snap-shot)
IGARSS 2011 Vancouver 10/16
11. •Remote
•Sensing
•Laboratory
The error model (iv)
Correlation denormalization: PMS gain and correlator loss are measured in-
flight well within requirements: amplitude error < 1%
Correlator loss PMS gain error
5 0.5
4 0.4
0.3
RMS[%]
3
%
2 0.2
0.1
1
0
0 0 20 40 60
0 500 1000 1500 2000 2500 Receiver number
Test data start: 24-12-2009 00:44:39 to 25-12-200900:05:14
Baseline number
In-flight measured Correlation Loss ~1.5 % RMS gain error after Tph correction ~0.2 %
IGARSS 2011 Vancouver 11/16
12. •Remote
•Sensing
•Laboratory
Calibration periodicity (i)
Calibration must be accurate, but also stable within requirements
• Calibration time minimization: calibration parameters decomposed into
several terms according to their temporal behaviour.
Example: Fringe washing term:
The phase is decomposed into three terms:
Phase after the switch. Periodically calibrated (2-10 min)
Phase between antenna and switch. Ground measurement
Frequency response differences. Constrained by design
IGARSS 2011 Vancouver 12/16
13. •Remote
•Sensing
•Laboratory
Calibration periodicity (ii)
Several orbits in calibration mode used to test procedures and parameters:
temperature sensitivity, calibration period, residual error, etc
Example: PMS orbital gain drift
Low Tph sensitivity and Tph correction keeps PMS gain error well below the 1% requirement
IGARSS 2011 Vancouver 13/16
14. •Remote
•Sensing
•Laboratory
Minimization of residual image distortion
Residual errors on calibrated visibility samples are very stable: “black box”
TM (ξ ,η ) = G −1·V (u , v)
Image distortion (pixel bias) very stable (residual antenna errors)
SMOS brightness temperature maps can be modeled as given by a
pushbroom radiometer with a real aperture radiometer pointing to each pixel
Multiplicative mask (*) Flat Target Transformation
Measured by ocean views (a weighted differential image)
at constant incidence angle Measured by deep sky imaging
(*) IGARSS 2011
IGARSS 2011 Vancouver 14/16
15. •Remote
•Sensing
•Laboratory
Conclusion: nested calibration
MIRAS calibration is a complex combination of procedures,
arranged in a "Russian doll" fashion
Parameter corrected at different subsystem level, at different calibration rates
Example: Offset
• Samplers threshold • Self-calibration correction at digital correlation level in
a per snap-shot basis (1.2 s).
bias
• PMS bias • 4 point calibration: correction at denormalization level
by weekly correlated noise injection.
• Internal signal coupling • U-noise/long calibration: correction at visibility level.
Monthly uncorrelated noise injection (1 orbit averaging)
• External (antenna) • Flat Target Transform: correction by means of deep sky
coupling. views (yearly) at brightness temperature level (inversion)
IGARSS 2011 Vancouver 15/16
16. •Remote
•Sensing
•Laboratory
SMOS brightness temperature
measurement and end-to-end
calibration
End
IGARSS 2011 Vancouver 16/16
