SIMO系统辅助变量最小二乘盲辨识方法

辅助变量辨识方法是一类重要的辨识方法,然而对于盲辨识,系统输入未知,辅助矩阵的选择就成了难题。针对盲辨识领域研究最多的单输入多输出(SIMO)系统,利用辅助变量方法研究相应的盲辨识方法,其基本思想是联立其中两个子系统进行辨识,利用其他子系统的输出来构造辅助矩阵,从而提出了辅助变量最小二乘盲辨识方法,来获得系统参数估计。还给出所提算法的递推形式,并进行了收敛性分析。仿真例子验证了所提方法的有效性。

Instrumental variable least squares blind identification for SIMO systems

As an important identification method,the instrumental variable method can give the unbiased parameter estimation for systems with colored noises and unknown noise models.The key is how to choose the instrumental variables to generate the instrumental matrices.In the traditional identification approaches with known input signals,the instrumental variables/matrices are formed by using the inputs,but for blind system identifcation,difficulty arises in that the system inputs are unavailable.For single-input,multi-input systems,this paper studies the corresponding blind identification methods using the instrumental variable technique.The basic idea is to identify two combined subsystems simultaneously using the outputs of the third subsystem as the instrumental variables/matrices and presents the instrunmental variable least squares(IVLS) blind identification algorithm and its recursive form.The convergence of the algorithm is also analyzed.A simulation example is included.