Single channel time-varying amplitude LFM interference blind separation using MHMPSO particle filtering

A new approach is proposed for single channel blind signal separation(SCBSS) problem of communication signal and time-varying amplitude LFM interference based on Metropolis-Hastings mutation particle swarm optimized particle filtering (MHMPSOPF). The proposed algorithm aims to obtain the maximum a posterior (MAP) estimate of communication code and the unknown parameters using particle filtering by establishing the state space model for the interfered signal, Specially, in order to overcome the sample impoverishment problem, particle swarm optimized is introduced to the re-sampling process in particle filtering(PF). In such a way, the number of needed particles is reduced and the variety of particles is retained during the sequential estimation process, moreover, the proposed algorithm has superior performance under time-varying amplitude LFM interference. Simulation results show that the method is effective to separate communication signal and interference when the ISR is less than 20dB and SNR is more than 14dB.