基于MPSO粒子滤波的单通道扰信盲分离算法

Single-channel blind separation of communication signal and interference based on MPSO particle filtering

针对单通道接收情况下通信信号与干扰盲分离的难题,提出了一种基于变异粒子群优化粒子滤波的单通道扰信盲分离新算法。首先建立了受扰通信信号的状态空间模型,并利用变异粒子群重采样粒子滤波进行通信码元和未知参数的联合最大后验估计,有效改善了标准粒子滤波中存在的粒子退化现象,在减少所需粒子数量的同时,又保持了序贯估计过程中粒子集合的多样性和优质性,使新算法在干信比较大时也能保持较好的分离性能。仿真实验表明,对单音干扰,在干信比等于30dB,信噪比大于15dB的条件下,新算法可以有效地从单路接收的受扰信号中分离出通信信号与干扰。

A new approach was proposed for single channel blind separation problem of communication sig- nal and interference based on mutation particle swarm optimized particle filtering （MPSOPF）. The pro- posed 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 jammed signal. To overcome the sample impoverishment problem, particle swarm optimized was introduced to the re-sam- piing process in particle filtering. In such a way, the number of the needed particles is reduced and the va- riety of particles is retained during the sequential estimation process, and moreover, the proposed algo- rithm has better performance under larger interference-signal-ratio（ISR）. Simulation results show that the method is effective to separate communication signal and interference when the ISR is less than 30dB and SNR is more than 15 dB.