A novel approach of blind separation of communication signal and interference is proposed for only one single-channel observation signal obtained and low signal noise ratio (SNR). The proposed algorithm aims to obtain the maximum a posterior (MAP) estimates of communication code and the unknown parameters using particle filtering by establishing the state space model for the observation signal, Specially， in order to overcome the sample impoverishment problem and estimate iteratively the particles that have more important weigh, genetic operation is introduced to the re-sampling process in particle filtering. In such a way, the number of needed particles is reduced and the variety of particles is retained during the sequential estimation process. Simulation results show that the proposed algorithm has superior performance than the classical particle filtering, and the method can effectivly separate communication signal and interference when the interference signal ratio (ISR) is less than 15 dB and SNR is more than 10 dB.