IGARSS11 End-to-end calibration v2.pdf

IGARSS 2011 Vancouver

•Remote•Sensing•Laboratory

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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



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Aperture Synthesis Interferometric Radiometer

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):

( )( )

ηξ

η−ξ−

−ηξ>==< 2

22

phB*21 ,F

1

T,T)t(b)t(b)v,u(V F

The Soil Moisture & Ocean Salinity Earth Explorer Mission (ESA)

• 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

(SMOS artist’s view, courtesy of EADS-CASA Space Division, Spain)

Launched November 2009



Simplified block diagram of a single baseline

antenna 1

antenna 2

antenna planes

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= Ak Ajsys sysAkj kj

kj

T TV M

G

Visibility sample at the antenna plane

MIRAS measures normalized correlations:

Mkj

Fringe Wash function at the origin

System temperature at antenna plane A

PMS

offAsys

k

kkAk G

vvT

−=

Tsys measured by PMS(Power Measurement System)



Before applying the "black box" approach MIRAS raw measurements (voltages and correlations) require a comprehensive error correction process

IRad calibration

1. Relative calibration (image distortion)

2. Absolute calibration(Level)

Interferometric radiometer calibration

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SMOS calibration scheme can be described from different points of view

1. Calibration

parameter

• Visibility amplitude, phase, offset• Reference radiometer (absolute amplitude)• Antenna errors (image distortion)

2. Instrument

configuration

• Internal: Correlated/uncorrelated noise injection• External: Flat target transformation/Reference radiometer• Ground: Image Validation Tests/ Factory parameters

3. Calibration

periodicity

• Snap-shot: self-calibration• Weekly: PMS offset (4 point cal)• Monthly: Reference radiometer/U-offset/FWF parameters• Yearly: Flat Target/thermal sensitivity/Heater parameters• Stable: Ground tests

SMOS calibration

An interferometric radiometer requires a complex calibration scheme!!!



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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



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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



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The error model (i)

I/Q sam

plingw

ith1 Bit / 2 Level

correlators

kI

kQ

jI

jQ

jk II

jk IQ

Digital correlation

-Sampling offset

-Quadrature error

-Non -linearity

SELF-CALIBRATION

Ideal complex normalized correlation

r ikj kj kjM M jM= +

The combination of both hardware and software procedures turns a real subsystem that produces corrupted raw measurements into an ideal block easier to integrate in a higher level data flow scheme

Complex, zero offset, quadrature corrected, normalized correlation

(snap-shot)

1100101…

0101101…

1100111…

0111100…

IDEAL CORRELATOR

(normalized)



The error model (ii)Residual error assessment and iterative fine tuning of the error model has been a key approach to improve subsystem performance

-0.4 -0.2 0 0.2 0.4 0.6

-0.4

-0.2

0

0.2

0.4

0.6

ℜe[M] (cu)

ℑm

[M] (

cu)

With 1-0 and truncation error correction

Mean= -0.00061+0.00029i cuσ=0.029cu

AMIRAS: MIRAS:

Example: digital correlator offset

m≈10-3

σ ≈10-4m≈6·10-8

σ ≈3·10-6

-0.4 -0.2 0 0.2 0.4 0.6

-0.4

-0.2

0

0.2

0.4

0.6

ℜe[M] (cu)

ℑm

[M] (

cu)

With 1-0 correction

Mean= -0.21-0.22i cuσ=0.03cu

m≈2·10-5

σ ≈3·10-6MIRAS:

avg ~12havg ~12havg~1min

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The error model (iii)Correlation denormalization: a PMS placed at each LICEF measures System Temperature and correlation loss

Linear, zero offset, temperature corrected,

power detector

(snap-shot)

IDEAL DETECTOR



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The error model (iv)Correlation denormalization: PMS gain and correlator loss are measured in-flight well within requirements: amplitude error < 1%

0 500 1000 1500 2000 25000

1

2

3

4

5

Baseline number

%

Correlator loss

0 20 40 600

0.1

0.2

0.3

0.4

0.5

Receiver number

RM

S[%

]

PMS gain error

Test data start: 24-12-2009 00:44:39 to 25-12-200900:05:14

In-flight measured Correlation Loss ~1.5 % RMS gain error after Tph correction ~0.2 %



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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



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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



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Minimization of residual image distortionResidual errors on calibrated visibility samples are very stable: “black box”

SMOS brightness temperature maps can be modeled as given by a pushbroom radiometer with a real aperture radiometer pointing to each pixel

( ) 1, · ( , )−=MT G V u vξ η

Flat Target Transformation

(a weighted differential image)

Measured by deep sky imaging

Multiplicative mask (*)

Measured by ocean views

at constant incidence angle

Image distortion (pixel bias) very stable (residual antenna errors)

(*) IGARSS 2011



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Conclusion: nested calibrationMIRAS calibration is a complex combination of procedures, arranged in a "Russian doll" fashion

Example: Offset

Parameter corrected at different subsystem level, at different calibration rates

• Samplers threshold

bias

• Self-calibration correction at digital correlation level in a per snap-shot basis (1.2 s).

• 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) coupling.

• Flat Target Transform: correction by means of deep sky views (yearly) at brightness temperature level (inversion)



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SMOS brightness temperature measurement and end-to-end

calibration

End

Technology

IGARSS11 End-to-end calibration v2.pdf