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In this paper, different methods are proposed for the detection and mitigation of the undesirable effects of radio-frequency interference (RFI) in microwave radiometry. The first of these makes use of kurtosis to detect the presence of non-Gaussian signals, whereas the second imposes a threshold on the standard deviation of brightness temperatures in order to distinguish natural-emission variations from RFI. Finally, the third approach is based on the use of a threshold applied to the third and fourth Stokes parameters. All these methods have been applied and tested, with the cooperative airborne radiometer for ocean and land studies radiometer operating in the L-band, on the data acquired during airborne campaigns made in the spring of 2009 over the southwest of France. The performance of each approach, or of two combined approaches, is analyzed with our database. We thus show that the kurtosis method is well suited to detect pulsed RFI, whereas the method based on the second moment of brightness temperatures seems to be better suited to detect continuous-wave RFI in airborne brightness-temperature measurements.