Interference Suppression Based on Single-channel Blind Source Separation in Weather Radar

The interference suppression is an eternal issue in radar system. In this paper, we first proposed a novel single-channel blind source separation (SBSS) algorithm which overcomes the limitation of traditional BSS method, and then the novel SBSS algorithm was performed to weather radar in interference suppression. The proposed SBSS method is inspired by the recently proposed variational mode decomposition (VMD) and the theory of sparse component analysis (SCA). The VMD algorithm was implemented to decompose the single-channel signal into two-channel signals and the improved SCA method was utilized to signal separation with under-determined situation. The numerical results of SBSS demonstrate that the source signals are preeminently retrieved from a single observed mixture. The algorithm is successfully applied to Doppler weather radar with interference of bird. Simulation results showed that the meteorology echo signal and interference signal are obviously separated. In addition, the SBSS algorithm also can be applied to multipath separation, signal denoising and some other situation.