利用粒子流滤波的单通道BPSK信号盲分离算法
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赵知劲(1959-),女,教授,博士生导师,研究方向:认知无线电、通信信号处理、自适应信号处理等,E-mail:zhaozj03@hdu.edu.cn;吴棫(1991-),男,硕士研究生,研究方向:信号处理,E-mail:waynegeek@qq.com。

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国防科技重点实验室基金资助项目。


Blind Separation Algorithm of Single Channel BPSK Signals Using Particle Flow Filtering
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    摘要:

    由于粒子滤波本身的"粒子贫化"问题,导致基于传统粒子滤波的单通道信号盲分离算法分离性能恶化以及计算量较大,本文提出了一种基于粒子流滤波的单通道BPSK信号盲分离新算法。根据由两路BPSK信号混合的单通道信号,构造了测量方程和状态方程。然后,通过将状态空间中服从先验分布的粒子移动到其对应的后验分布上,实现了粒子更新,其不同于粒子滤波采用重采样来更新粒子,避免了"粒子贫化"现象发生。最后,采用一种基于弱解形式的粒子流滤波器实现BPSK信号的盲分离。计算机仿真结果表明,与粒子滤波算法相比本文算法具有更低的误码率和计算复杂度。

    Abstract:

    Since ‘particle impoverishment’ of the particle filter deteriorates the performance of the single channel blind signal separation based on traditional particle filtering and its huge calculation, a new single channel blind BPSK signal separation algorithm based on particle flow filtering is proposed. Firstly, according to single channel signal of mixing two BPSK signals, a measuring equation and a state equation are built. Secondly, particles are updated through moving the particles in state space which obey the prior distribution to its corresponding posterior distribution, which is different from using resampling to update particles in particle filtering (PF), thereby avoiding the ‘particle impoverishment’ phenomenon caused by re-sampling in PF. Lastly a weak solution based particle flow filter is used to achieve BPSK blind signal separation. Computer simulation results show that compared with particle filtering algorithm the new algorithm has the lower bit error rate and computational complexity.

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赵知劲, 吴棫.利用粒子流滤波的单通道BPSK信号盲分离算法[J].数据采集与处理,2018,33(3):409-415

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  • 收稿日期:2016-01-26
  • 最后修改日期:2017-01-09
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  • 在线发布日期: 2018-07-09