ElectroScience Lab

Studies of Radio Frequency Interference in SMOS Observations

IGARSS 2011

Joel T. Johnson and Mustafa Aksoy

Department of Electrical and Computer Engineering

ElectroScience Laboratory

The Ohio State University

Vancouver, Canada

29th July 2011

*SMOS data provided by the European Space Agency

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Motivation

Radio Frequency Interference (RFI) a major concern for L-band (1400-1427 MHz) microwave radiometry

ESA’s SMOS mission experiencing significant RFI since launch Nov 2009

RFI expected for NASA’s Aquarius (now in orbit) and SMAP (launch ~ 2014) Important to understand RFI environment to plan for these missions SMAP will include a digital backend to enhance RFI detection/mitigation,

but need to assess expected performance

Examine properties of RFI in SMOS observations Primarily with L1C data but selected L1B examples also shown Some “artifacts” caused by strong sources and SMOS system properties

Try to reduce artifacts to see RFI “truth” Compile statistical information, “low level” RFI of particular interest Emphasize North America since RFI here is more “low level”

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Outline

SMOS observations and datasets

Initial examination of statistics

RFI artifacts and reduction strategies

“Artifact reduced” statistics

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SMOS Basics

ESA’s Soil Moisture and Ocean Salinity (SMOS) mission has operated an L-band interferometric radiometer in space since Nov 2009

Provides multi-angular observations for each pixel (including SMAP’s 40o)

SMOS measurement properties:– native time resolution ~ 1.2 sec, a single frequency channel– Tb’s (H, V, U, 4) give power levels (fullband, time averaged) and location– Interferometric focusing can cause some sidelobes and aliasing of RFI sources

4

~ 40 degrees portion of SMOS swath

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SMOS L1 Data Products

L1A: calibrated visibilities (i.e. correlations): Not using at present L1B: calibrated Fourier components of brightness temperature

– Can construct brightness temperature image by applying appropriate window function then performing FFT

L1C maps L1B data onto an Earth-fixed grid– Reordered by grid point, multiple angles at each grid point– Expected Tb accuracy and resolution also included for each angle at a

given grid point

Alias-FreeField of View

Plus extendedAlias-FreeField of View

Sidelobes ofAliased RFISourcesCan impactAF-FOV

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Initial Examination of Statistics: 2/9/11-3/8/11, %Th>350 K, 40o+/-2.5o

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Initial Examination of Statistics: 2/9/11-3/8/11, %Th>350 K, 40o+/-2.5o(log scale)

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Initial Examination of Statistics: 2/9/11-3/8/11,Th Max, 40o+/-2.5o

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Initial Examination of Statistics: 2/9/11-3/8/11, sqrt(Tu^2+T4^2) Max, 40o+/-2.5o

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Where do “artifacts” come from? Sidelobes from strong sources spread into rest of snapshot

Worse because these sources may be outside L1C field of view

Sources appear multiple times outside of FOV due of aliasing

Sources “sit” on Earth horizon: atmospheric ducting mechanism?

Alias-FreeField of View

Plus extendedAlias-FreeField of View

Sidelobes ofAliased RFISourcesCan impactAF-FOV

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L1B/L1C Movie Illustrating Artifacts

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L1B/L1C Movie Illustrating Artifacts (Descending)

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Reducing Artifacts Sources in forward part of swath more problematic

– Ascending more problematic when large sources are to the North– Descending more problematic when large sources are to the South– Use only descending observations for North America

Outer parts of swath more susceptible to corruption– Using only the AF-FOV helps some, but still some issues– Reduce swath further using a limit on accuracy

Try to throw out “bad” snapshots entirely– Look at time series of boresite accuracy (related to mean image brightness)– Use a “pulse” detection algorithm to discard outliers

Examine RFI in remaining data: should have reduced artifacts– Some large RFI sources not causing artifacts may also be discarded

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Swath and Snapshot Reduction Examples Include only points whose accuracy is within

10% of the boresite value (limits swath)

Apply “pulse” detection algorithm and a threshold to boresite accuracy to detect“bad” snapshots and discard

Portion of swathmeetingaccuracy limits

“Bad” snapshots detected by pulse algorithm are entirely discarded

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Image Before/After Artifact Reduction Max of H pol (all angles): Descending only North America, Feb 2011

“True” RFI sources more apparent with artifacts reduced

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Max of sqrt(Tu^2+T4^2) (all angles): Descending only North America, Feb 2011

Higher sensitivity of polarimetric channels shows more sources, although likely some artifacts remain

Image Before/After Artifact Reduction

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SMOS Tb CCDF Over SMAP Mask (40 deg) H pol, Ascending only, 1/14/11-2/28/11

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Conclusions SMOS experiencing significant corruption due to RFI

– Difficult to detect and remove, especially low-level RFI– Many approaches being explored: point source removal (L1B),

multi-angle or polarimetric (L1C), geophysical anomaly (L2)

Impacted not only by real sources but also by “artifacts”– Sidelobes of both real and aliased sources, esp. those on horizon– Limiting swath, ascending/descending, and throwing out “bad”

snapshots can reduce artifacts

Statistics of artifact reduced data still show significant RFI presence– Examine this dataset to assist in SMAP planning– Explore potential low-level RFI detection strategies in future work– Also matchups with previous airborne dataset in the USA