一种波束域子带盲源分离新方法

针对传统时域盲源分离算法对宽带不适用、计算量较大和对信噪比(SNR)变化敏感这三个问题，提出了一种波束域子带盲源分离(BSS)方法：它以子带分解的方法实现了时域盲源分离算法在宽带情形下的扩展；利用波束转换实现降维运算，大大减少了运算量和提高了算法的稳健性。仿真结果表明，与阵元域盲源分离算法相比，新方法具有低信噪比时较好的源信号波形估计能力。在源数目等先验信息未知的情况下，与Root-Music高分辨算法具有近似的角度估计性能。

Novel beamspace blind source separation method based on sub-band decomposition

Concerning the problems of the blind source separation algorithm that is not suitable for the broadband, complex computation, and being acute to various Signal Noise Ratio (SNR), a beamspace Blind Source Separation (BSS) method based on sub-band decomposition was proposed. The method of sub-band decomposition was used to realize the expansion of blind source separation under broadband condition, and beam transforming was used to reduce the amount of calculation. Simulation results demonstrate that the proposed method exhibits good source signal estimation capability. Even without any prior knowledge, it has the same performance as Root-Music high resolution algorithm.