An improved clean algorithm for RFI mitigation in aperture synthesis radiometers

Abstract

The SMOS mission is developed for monitoring the surface soil moisture and ocean salinity by a two dimensional L-band synthetic aperture interferometric radiometer. However, artificial sources emitting in the protected L-band are contaminating the retrievals of the soil moisture and ocean salinity from the measurements. To mitigate the RFIs' impacts, the classical CLEAN algorithm was introduced and works well for most isolated point RFI sources. However, in presence of interactions between different RFI sources, the performance of the classical CLEAN algorithm will deteriorate. Thus, in this work, we present an improved CLEAN algorithm to compensate for the RFIs' impacts more accurately in presence of interactions from adjacent RFI sources. It adds back one previously detected RFI to the cleaned map and then reestimates the parameter of this RFI source. Numerical studies using synthetic SMOS data have been carried out to demonstrate that the proposed algorithm outperforms the classical CLEAN algorithm in presence of interactions between RFI sources.