基于改进快速子空间迭代跟踪的部分自适应STAP算法

Partial Adaptive STAP Algorithm With Improved PAST Subspace Tracking Technique for Clutter Suppression

针对部分空时自适应(STAP)处理的特征值分解(EVD)影响杂波抑制的实时处理性能,提出了基于改进快速子空间迭代跟踪(PAST)的部分自适应STAP算法。该方法首先在PAST处理的基础上,对正交PAST方法进行改进,得到改进后的PAST(MPAST)方法;然后将MPAST方法应用于计算部分自适应STAP算法的特征子空间,从而有效提高STAP算法的收敛速度和降低自适应权矢量计算的运算量。仿真数据和MCARM实测数据分析表明,该方法能有效抑制待检测距离单元的杂波,并能在低计算复杂度下显著提高STAP处理的收敛速度。

The eigenvalue decomposition（ EVD） technique in conventional partial adaptive STAP algorithms is impractical for real- time processing because of the inherent computational complexity as large as that of the covariance matrix inversion. The projection approximation subspace tracking（ PAST） method can track the eigenvectors of clutter subspace efficiently with smaller complexity. Therefore,the partial adaptive STAP algorithm based on improved PAST subspace technique is proposed for clutter suppression in this paper,which can reduce both the computational complexity and the sample support significantly. The effectiveness of the proposed partial adaptive STAP algorithm is demonstrated by the simulated data and real MCARM data.