论文部分内容阅读
提出一种利用协方差矩阵的Ｔｏｅｐｌｉｔｚ特性，使估计的协方差矩阵成为Ｔｏｅｐｌｉｔｚ矩阵的方法，在低信噪比短数据流情况下，改善来波方向（ＤＯＡ）估计的性能，且不需增加乘法运算量．对ＭＵＳＩＣ算法和ＰＲＯＥＳＰＲＩＴ算法进行了分析并作了计算机仿真，仿真结果表明：利用Ｔｏｅｐｌｉｔｚ特性后，ＭＵＳＩＣ算法谱峰幅度增大，波谷相对波峰的深度增加，这将有利于目标的分辨；并可减小低信噪比情况下ＭＵＳＩＣ算法和ＰＲＯＥＳＰＲＩＴ算法ＤＯＡ估计的方差．
A new method is proposed to make use of the Toeplitz property of the covariance matrix so that the estimated covariance matrix becomes a Toeplitz matrix. In the case of low signal-to-noise ratio short data stream, the DOA estimation performance is improved without multiplication Computation. The MUSIC algorithm and PROESPRIT algorithm are analyzed and simulated. The simulation results show that the MUSIC algorithm increases the spectral peak amplitude and the depth of the trough relative to the peak, which is beneficial to the target resolution. Can reduce the variance of DOA estimation of MUSIC algorithm and PROESPRIT algorithm under low S / N ratio.