一种改进的SMI旁瓣干扰抑制算法研究

摘要

SMI algorithm is commonly used in adaptive sidelobe cancellation.With low-snapshot data,the small eigenvalues of the covariance matrix spread,and thereby causing that the level of adaptive beam sidelobe increases.To solve this problem,an improved method of SMI algorithm is proposed.Through getting covariance matrix from sliding average of the snapshot data,this method makes the spread of the small eigenvalues decrease,and can obtain low sidelobe,so it makes the SMI algorithm suitable for low-snapshot data.%采样矩阵求逆（SMI）算法是常用的自适应旁瓣对消算法。针对在低快拍下数据协方差矩阵的小特征值扩散,进而引起自适应波束副瓣升高的问题,提出了一种改进SMI算法的方法。该方法通过快拍数据的滑动平均获得协方差矩阵,使协方差矩阵小特征散布变小,能够很好地抑制副瓣电平,从而使算法适用于低快拍数据。