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SMOS RFI – June 20161
Earth Exploration Satellite Service (passive) at 1.4 GHz :
the SMOS experience.
Yann H. Kerr*, Vincent Meens**,Philippe Richaume*, Eric Anterrieu*, François Cabot*, Jean Pla**,
Alexandre Vallet***
* CESBIO **CNES ***Agence Nationale des FRequences
SMOS RFI – June 20162
The SMOS mission and observation system in brief
• Radio-interferometer operating in the L-band @ 1413MHz within the ITU protected 1400 –1427 Mhz band (ITU RR 5.340)
• 69 elementary antennae (LICEF) distributed along Y shape arms• 3dB beamwidth= ~70° = whole Earth + sky• The image reconstruction forms synthetic antennas ~ 2.5° beam
= ~40 km on the Earth at 755 km altitude Allows Brightness Temperatures (BTs) images (SNAPSHOTs) over 1500km x 1000
km every 1.2 sec largely overlapping Full polarimetic BTs in polarization XX, YY and XY 2.5K to 5K of radiometric accuracy
• Boresight tilted 32° ahead Asymmetric Field Of View (FOV)
Nadirdirector cosine
SMOS motion
SMOS RFI – June 20163
•Each integration time, (2.4 s) a full scene is acquired (dual or full pol)
•Average resolution 43 km, global coverage•A given point of the surface is thus seen with several angles
•Maximum time (equator) between two
acquisitions 3 days
Principle of operations
SMOS FOV; 755 km altitude
P. Waldteufel, 2003
SMOS RFI – June 20164
SMOSPrinciple and key points
SMOS RFI – June 20165
Why L Band – Why SMOS
L band only protected frequency to access soil moisture and Sea surface salinity
SMOS used for Weather forecast Extreme event prediction (drought index, rainfall estimates) Hurricane monitoring Flood /flash flood alerts Irrigation and water management Sea ice ….
Stay tuned http://www.cesbio.ups-tlse.fr/SMOS_blog/
SMOS RFI – June 20166
The RF Interference environment
frequency
Active band
Unwanted emissions
OoB domain Spurious domain
Passive band
1427 MHz1400 MHz
Wanted signal(Brightness temperature)
Interfering signals
SMOS uses only 19 MHz of the available 27 MHz “to be on the safe side”
SMOS RFI – June 20167
Radio frequency interferences examples as seen by SMOS• Brightness Temperatures usually far too high – but not necessarily all the time• As much important, brightness Incidence angle profile can be severely damaged
Soon after launch the protected L-band did not appear so protected
1000 K TBX1040 K TBY
327 K TBX362 K TBY
320 K TBX306 K TBY
43200 K TBX5683 K TBY
300K
240K
180K40K
-30K0K
64000K
10000K
0K
-2500K
SMOS RFI – June 20168
Tilted antenna plane asymmetric RFI impacts depending on orbit passes
http://www.cesbio.ups-tlse.fr/SMOS_blog Data RFI Monitoring RFI Probability
30%
00%
05%
10%
15%
20%
25%
Ascendingorbits
P Richaume
SMOS RFI – June 20169
http://www.cesbio.ups-tlse.fr/SMOS_blog Data RFI Monitoring RFI Probability
Tilted antenna plane asymmetric RFI impacts depending on orbit passes
P Richaume30%
00%
05%
10%
15%
20%
25%
Descendingorbits
SMOS RFI – June 201610
RFI impact on retrievals total destruction of data to low level (halo) contributions giving erroneous values
This situation started 20120822 and lasted for several weeks
SMOS RFI – June 201611 J. Boutin
SMOS RFI – June 201612 J. Boutin
SMOS RFI – June 201613
SMOS Brightness Temperature observations in Japan
3 Sep 11 21 Sep 11 9 Oct 11 27 Oct 11 9 Oct 11 27 Oct 11
1. SMOS revisits Japan twice every 3 days (one in descending direction + one in ascending direction). A clear change was observed between the
21st September and the 24th September.
24 Sep 11 6 Oct 11
SMOS RFI – June 201614
The Japanese RFI case
0 20 40 60 800
5
10
15
20
25
30
Months from January 2010
Num
ber o
f RFI
RFI #testeventsmax per pass
3G TV-2 4G TestTV-1
SMOS RFI – June 201615
RFI Detection approaches
Sources can be quite different Radars TV Mobile Transmission links
All based on physical signals Brightness temperature level (unphysical)
o Many different criteria (overall scene temperature, variations with surroundings, temporal stability, etc… )
Abnormal angular signatures or polarisations Etc..
And accurate geolocalisation of sources when strong and notdiffused (Between a few 100 m do 4-5 km)
SMOS RFI – June 201616
RFI Action status
Continuous activities Regular updating of RFI Continuous update of maps on the blog Continuous tracking of sources as per requests Monthly meetings High accuracy localisation (EA – IRAP)
Coordination with other entities NASA SMAP and Aquarius satellites Informing through ESA administrations of RFI sources on their
territories Search for improvements
Using the 6 years to get accurate (?) position on permanent sources (PR)
Use of other indicators to fine tune RFI pollution (PR-AlM)
SMOS RFI – June 201617
R. Oliva
SMOS RFI – June 201618
R. Oliva
SMOS RFI – June 201619
Evolution of achievements in Switching Off RFIs (R. Oliva)
- Improved detection algorithms have allowed ESA to provide better information to the national authorities.
- This was reflected in the corresponding improvement in in the situation in Europe. - The current limitation is the lack of response of several countries around the World.
SMOS RFI – June 201620
Conclusion• RFI: a real issue
• At best diminishes data quality• Often makes « holes » in the data set• No geophysical retrievals possible in some areas
• Good news• SMOS « discovered » the amplitude of the problem so Aquarius
and SMAP could capitalise on it and improve detection BUT RFI still present and data quality degraded or data missing
• Several souces were suppressed and progresses are still made
• Bad News• Situation evolves slowly• Detection is tricky considering the number of source types
• Detection algorithms well identified and starting to be accurate
• Coordinated actions with complementary systems i.e., SMOS +SMAP. Work required at National and international level
SMOS RFI – June 201621
Example of Hydrology from SMOS
A. Mialon, S. Bircher
SMOS RFI – June 201622
An example of SMOS Flood Risk Forecast
RainfallforecastRainfallforecast
SMOS SM L3 products
Rainfallprobabilities
Rainfallprobabilities
SMOS Soilmoisture
probabilities
SMOS Flood Risk
SMOS Flood Risk
PrecipitationFlood Risk
PrecipitationFlood Risk
Flood Risk(Precip + SMOS)
Flood Risk(Precip + SMOS)
Leveraging flood risk based on SMOS soil moisture knowledge
Al Bitar A., Chone A., S. K. Tomer, Kerr Y. CESBIO
Methodology
SMOS RFI – June 201623
An example of SMOS Flood Risk Forecast
Al Bitar A., Chone A., S. K. Tomer, Kerr Y. CESBIO