On the Potential of Empirical Mode Decomposition for RFI Mitigation in Microwave Radiometry

Abstract

Radio Frequency Interference (RFI) is an increasing problem particularly for Earth Observation using Microwave Radiometry. RFI has been observed, for example, at L-band by the ESA’s SMOS (Soil Moisture and Ocean Salinity) Earth Explorer and by NASA’s SMAP (Soil Moisture Active Passive) and Aquarius missions, as well as at C-band by AMSR-E and AMRS-2; and at 10.7 GHz and 18.7 GHz by AMSR-E, AMRS-2, WindSat and GMI [1], [2]. Therefore, systems dedicated to interference detection and removal of contaminated measurements are nowadays a must in order to improve the radiometric accuracy and reduce the loss of spatial coverage caused by interference. In this work, the feasibility of using the Empirical Mode Decomposition (EMD) technique for RFI mitigation is explored. The EMD, also known as Hilbert-Huang Transform (HHT), is an algorithm that decomposes the signal into Intrinsic Mode Functions (IMF). The achieved performance is analyzed, and the opportunities and caveats that this type of methods present are described. EMD is found to be a practical RFI mitigation method, albeit presenting some limitations, and a considerable complexity. Nevertheless, in some conditions, EMD exhibits a better performance than other commonly used methods (such as frequency binning). In particular, it has been found that EMD performs well for RFI affecting the < 25% lower part of the Intermediate Frequency (IF) bandwidth.