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本文详细地研究了ARMA信号源模型参数(即模型的零点和极点位置)变化对采用递归最大似然(RML)算法自适应谱估值器估计性能的影响。指出在合理的数据长度内,这种方法适用于模型的零点和极点充分分离的情况。提出了一种可获得高分辨率谱估计的高阶估值器方法。
In this paper, the influence of ARMA signal source model parameters (ie, zero and pole location) on the estimated performance of adaptive spectral estimators using Recursive Maximum Likelihood (RML) algorithm is studied in detail. It is pointed out that this method is suitable for the case that the zero point and the pole of the model are sufficiently separated within a reasonable data length. A high-order estimator method for high-resolution spectral estimation is proposed.