实值循环ESPRIT算法

Real-valued cyclic ESPRIT Algorithm

为了降低循环ESPRIT算法的计算复杂度,提出了一种实值循环ESPRIT算法,通过构造了循环自相关矩阵的数据模型,使其具有厄尔米特特性,将复数自相关矩阵映射成实值矩阵,通过实值分解降低了计算量,而且具有信号选择特性。由于空间平滑技术的引入,较好地解决了多径传播环境中信号高度相关问题。仿真实验结果证明,与循环ESPRIT算法相比,该算法适应多径传播环境,具有计算量小和性能好等特点。

To reduce the computational complexity of cyclic ESPRIT, a real-valued cyclic ESPRIT algorithm with signal-selective property was proposed by reconstructing the data model of the cyclic covariance matrix with Hermitian property, which achieved a substantial reduction of the computational complexity via real-valued decomposition technique. Due to spatial smoothing, this algorithm had a better performance in the presence of multipath propagation. Finally simulation results that this algorithm, comparing with cyclic ESPRIT, adapts to multipath environment and has features of better performance and low computational complexity are obtained.