RFI Localization via Generalized Augmented Covariance Matrix Reconstruction

The performance of the Soil Moisture and Ocean Salinity (SMOS) mission headed by the European Space Agency (ESA) deteriorated due to the influence of radio-frequency interferences (RFIs). Accurate location of RFI sources is essential for effectively improving the SMOS mission performance. This paper proposes a new RFI location method based on generalized augmented covariance matrix reconstruction (GACMR). This method relaxes the constraint of the sparse array expansion criterion to obtain the generalized augmented covariance matrix (GACM). After that, a generalized reweighted strategy is introduced to reconstruct the GACM. Experimental results demonstrate that compared with some existing RFI localization methods, this proposed method not only can effectively find weak sources and reduce artifacts but also has better localization accuracy.