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![•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](https://image.slidesharecdn.com/igarss11-end-to-end-calibration-v2-110728105437-phpapp02/85/IGARSS11-End-to-end-calibration-v2-pdf-9-320.jpg)
![•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](https://image.slidesharecdn.com/igarss11-end-to-end-calibration-v2-110728105437-phpapp02/85/IGARSS11-End-to-end-calibration-v2-pdf-11-320.jpg)
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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
- 6. •Remote •Sensing •Laboratory SMOS calibration modes classification 1. Internal Calibration • Relative calibration (internal reference) • Periodical correlated/uncorrelated noise injection • Correction of orbital/seasonal parameter drift 2. External Calibration • Absolute calibration (external reference) • Monthly sky views • Correction of seasonal parameter drift 3. Ground Calibration • Relative calibration • Ground characterization of stable parameters • Correction of manufacturing dispersion IGARSS 2011 Vancouver 6/16
- 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