RFI detection and mitigation for microwave radiometry with an agile digital detector

Ruf, Christopher S.; Gross, S.M.; Misra, Sidharth

doi:10.1109/tgrs.2005.861411

Cited by 167 publications

(98 citation statements)

References 10 publications

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“…Kurtosis criterion has been largely used for radiometric measurements e.g. [Ruf et al, 2006;Skou et al, 2010] but partly fails on our data since high T A remains despite normal values of kurtosis (excess T A up to 60 K in V-pol and 30 K in H-pol). In Appendix A, we proposed a modified algorithm for ocean radiometric measurements, which is more restrictive than the previous one.…”

Section: Carols Radiometric Datamentioning

confidence: 93%

“…One type of method largely used for radiometric measurements [Ruf et al, 2006;Skou et al, 2010] is based on a threshold applied on the kurtosis of the antenna temperature distribution. Applied on our CAROLS raw data (kurtosis estimated on a distribution of 139.400 samples per 1 ms integration intervals), it turned out to be not fully appropriate: indeed after rejection using this criterion, high CAROLS T A remain despite normal values of kurtosis (excess T A up to 60 K in V and 30 K in H on 1 ms measurements).…”

Section: Appendix A: Rfi Detection and Mitigation Algorithmmentioning

confidence: 99%

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Active‐passive synergy for interpreting ocean L‐band emissivity: Results from the CAROLS airborne campaigns

et al. 2014

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The impact of the ocean surface roughness on the ocean L-band emissivity is investigated using simultaneous airborne measurements from an L-band radiometer (CAROLS) and from a C-band scatterometer (STORM) acquired in the Gulf of Biscay (off-the French Atlantic coasts) in November 2010. Two synergetic approaches are used to investigate the impact of surface roughness on the L-band brightness temperature (Tb). First, wind derived from the scatterometer measurements is used to analyze the roughness contribution to Tb as a function of wind and compare it with the one simulated by SMOS and Aquarius roughness models. Then residuals from this mean relationship are analyzed in terms of mean square slope derived from the STORM instrument. We show improvement of new radiometric roughness models derived from SMOS and Aquarius satellite measurements in comparison with prelaunch models. Influence of wind azimuth on Tb could not be evidenced from our data set. However, we point out the importance of taking into account large roughness scales (>20 cm) in addition to small roughness scale (5 cm) rapidly affected by wind to interpret radiometric measurements far from nadir. This was made possible thanks to simultaneous estimates of large and small roughness scales using STORM at small (7)(8)(9)(10)(11)(12)(13)(14)(15)(16) ) and large (30 ) incidence angles.

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Section: Carols Radiometric Datamentioning

confidence: 93%

Section: Appendix A: Rfi Detection and Mitigation Algorithmmentioning

confidence: 99%

Active‐passive synergy for interpreting ocean L‐band emissivity: Results from the CAROLS airborne campaigns

et al. 2014

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“…These signals are random processes and hence the pdf of the amplitude of this signal has a Gaussian distribution. The kurtosis algorithm for RFI detection developed by Ruf et al [3] takes advantage of the fact that almost all manmade sources would have a non-Gaussian distribution. RFI is detected by measuring the amount of deviation of the kurtosis parameter from normality.…”

Section: IImentioning

confidence: 99%

“…Detection purely depends upon the type and distribution of the man-made interfering source [4]. Any man-made interference with a near-Gaussian distribution would be impossible to detect in this manner [3].…”

Section: Vmentioning

confidence: 99%

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CoSMOS: Performance of kurtosis algorithm for radio frequency interference detection and mitigation

Misra

Kristensen

Søbjærg

et al. 2007

2007 IEEE International Geoscience and Remote Sensing Symposium

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Abstract-The performance of a previously developed algorithm for Radio Frequency Interference (RFI) detection and mitigation is experimentally evaluated. Results obtained from CoSMOS, an airborne campaign using a fully polarimetric L-band radiometer are analyzed for this purpose. Data is collected using two separate integration times, as a result of which sensitivity of the detection algorithm is measured. The impact of RFI on remotely sensed data over land and sea is also presented.

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In situ validation of sea surface temperatures from the GCOM‐W1 AMSR2 RSS calibrated brightness temperatures

Gentemann

Hilburn

2015

JGR Oceans

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Remote Sensing Systems AMSR2 v7.2 data from 25 July 2012 to 9 October 2014 are collocated with in situ sea surface temperature (SST) data. The RSS SST algorithm uses AMSR2 brightness temperatures calibrated using a methodology developed at RSS rather than using the standard JAXA AMSR2 product, which includes the JAXA calibration. The new RFI exclusion methodology used for the AMSR2 v7.2 data is described. Buoy data are quality controlled using an internal quality indicator. Daytime collocations with wind speeds of less than 6 m s 21 are excluded to avoid diurnal contamination of the results. A mean bias (AMSR2 minus in situ) of 20.04 K and standard deviation 0.55 K with 109,350 collocations is found. The geographical distribution of biases is investigated, with a small increase in biases found at higher latitudes. At lower SST the uncertainty increases and the bias. The dependencies of the bias and uncertainties on other geophysical variables are shown to be negligible. The time series of the bias and uncertainty show little variability, but a small seasonal dependence is determined to be related to a seasonal shift in wind speeds. Overall, the AMSR2 SSTs are of comparable quality to the AMSR-E SSTs and continue the climate microwave SST record that started in 1997.

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RFI detection and mitigation for microwave radiometry with an agile digital detector

Cited by 167 publications

References 10 publications

Active‐passive synergy for interpreting ocean L‐band emissivity: Results from the CAROLS airborne campaigns

Active‐passive synergy for interpreting ocean L‐band emissivity: Results from the CAROLS airborne campaigns

CoSMOS: Performance of kurtosis algorithm for radio frequency interference detection and mitigation

In situ validation of sea surface temperatures from the GCOM‐W1 AMSR2 RSS calibrated brightness temperatures

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