Non-stationary Interference Mitigation for GNSS Using Sparse Representation

Electromagnetic interference poses a threat to global navigation satellite systems (GNSS) used in various civilian applications. Sparse representation has been extensively studied for interference cancellation. However, dictionaries of non-stationary signals are difficult to construct due to their time-varying characteristic. Therefore, the mitigation of non-stationary interference is still a challenging issue. This paper proposes an adaptive dictionary construction approach for sparse representation of non-stationary interference. The proposed algorithm utilizes the non-stationary signal analysis tool, Wigner-Ville distribution (WVD), to provide prior knowledge. The overcomplete dictionary is constructed adaptively based on the instantaneous frequencies estimated from WVD. The proposed approach can reconstruct non-stationary interference successfully exploiting the adaptive dictionary. The simulation results confirm that the proposed interference suppression algorithm can successfully mitigate the interference and achieve GNSS signal acquisitions.