时变幅度LFM干扰下的单通道盲分离算法研究

Research on Single-Channel Blind Separation Algorithm for Time-varying Amplitude LFM Interference

  • 摘要: 针对时变幅度LFM干扰下的单通道通信信号与干扰盲分离问题,本文提出了一种基于遗传粒子滤波的单通道盲扰信分离新算法。该算法首先建立了受扰信号的状态空间模型,并利用粒子滤波得到通信码元和未知参数的最大后验估计。针对标准粒子滤波中存在的粒子退化现象,本文引入了遗传进化操作来迭代估计优质粒子,在减少了所需粒子数量的同时,加快了算法的收敛速度,使新算法在时变幅度LFM干扰的影响下具有较好的分离效果。非扩频通信信号仿真实验表明,新算法在干信比小于15dB,信噪比大于16dB的条件下,可以有效地从单路接收的受扰信号中分离出通信信号与LFM干扰。

     

    Abstract: A new approach is proposed for single-channel blind separation of communication signal and time-varying amplitude LFM. 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 interfered 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 during the sequential estimation process. Simulation results of nonspread spectrum communication signal show that, the method is effective to separate communication signal and LFM interference when the Interference-Signal- Ratio (ISR) is less than 15dB and SNR is more than 16dB.

     

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