基于伪信噪比最大化的盲源分离算法

针对电子战中各种信号混叠严重、难以分离的现象,提出一种新的瞬时线性混叠信号的盲源分离算法。该算法从独立信号完全分离时信噪比最大出发,用单位对称滑动权向量加权分离信号作为源信号,建立基于源信号和噪声信号协方差矩阵的伪信噪比目标函数,并将目标函数的寻优过程转换为求解广义特征值的问题。和经典的信息理论方法相比,该算法是一种全局最优的盲源分离算法,它不需要任何迭代运算,具有非常低的计算复杂度。仿真结果证明,该算法能够更加有效地分离线性混叠的雷达信号和通信信号。

Algorithm of blind source separation based on maximum pseudo-SNR

A novel instantaneous linear mixture blind source separation algorithm is proposed in view of that it is difficult to separate all kinds of signals mixed seriously in EW environment.The pseudo-signal to noise ratio function constructed by the covariance matrix of source signals and noises is built as an objective function,which is based on the theory that signal to noise ratio(SNR) is maximal when statistically independent source signals are completely separated.And the source signals are replaced by the processing of estimate signals with the unit symmetrical moving weight vector.Then the objective function is expressed by the generalized eigenvalues(GE) problem,and an unmixing matrix is achieved by solving the GE problem without any iterative.Compared with the typical information-theoretical approaches,this new optimal blind separation algorithm is a global with low computational complexity.Computer simulation demonstrates that this algorithm can separate the radar signals and communication signals effectively in the complicated environment.