无限方差噪声环境下的分数低阶空间时频盲源分离

对脉冲噪声α稳定分布环境下的时频分布进行了研究，改进了适合α稳定分布信号或强脉冲噪声环境的分数低阶时频分布方法，用分数低阶空间时频矩阵代替空间时频矩阵，基于时频盲分离算法提出了一种改进的分数低阶空间时频盲源分离算法，并归纳了算法步骤。通过对FLO-TF-UBSS算法和已有的TF-UBSS算法及MD-BSS算法进行详细比较，仿真结果表明，所提出的FLO-TF-UBSS算法有效的降低了信号的均方误差（MSE），能较好的对α稳定分布噪声环境下的非平稳信号进行盲分离，并实现了对实际的稳定分布舰船信号的盲提取，性能优于已有TF-UBSS算法和MD-BSS算法，且具有一定的韧性。 

Fractional Lower Order Spatial Time-Frequency Blind Source Separation In Infinite Variance Noise Environment

The traditional time-frequency distribution and bind source separation are poor performance in the impulsive noise with α-stable distribution environment. Time-frequency distribution in the presence of impulsive noise is investigated and the new time-frequency distributions which can work in α stable distribution environment are improved. Therefore, the traditional WVD time-frequency distribution are improved based on the stable distribution noise of non-stationary signal, we put forward a kind of fractional lower order pseudo FLO-PWVD time-frequency distribution which can be suitable for α stable distribution noise, and presented the fractional lower order pseudo spatial time-frequency matrix (FLO-MSTFM) concept, and so a new replaced bind source separation algorithm based on fractional lower order spatial time-frequency matrix is proposed, and the algorithm steps are summarized. Computer simulations show that the new algorithm has good performance to separate non-stationary signals in α-stable distribution environment and implement blind extraction of the α stable distribution signal, the MSE is less than TF-UBSS algorithm and MD-BSS algorithm in different α and GSNR.