文中介绍了一种基于时变自回归模型的归一化参数自适应匹配滤波算法。
In this paper, an algorithm of normalized parametric adaptive matched filter based on time-varying autoregressive model is introduced.
在此基础上建立时变序列预测公式及误差估计公式，给出其回归与时变自回归模型。
The prediction formula and its error estimation are also established. Its regression and time-varying autoregression model is presented.
结果表明，动态自回归模型时变参数（时变系数）的变化是有规律的，其增量大体上是一些简单周期函数的叠加。
The results showed that the change of time-varying parameters (coefficient) in dynamic AR model has a regularity. Its increments are piled up by some simple period functions.
文中给出RTVAR模型和GRTVAR模型参数的估计方法，并建立广义回归—时变自回归预测公式。
The parameter estimation of RTVAR and GRTVAR models and the GRTVAR prediction formulas are also established.
首先，采用改进的Y—W方程对TVARMA模型时变自回归部分系数进行估计，并计算残差序列；
Firstly, the modified Y-W equation was used to estimate the parameters of the time-varied auto-regressive part and the error signal;
首先，采用改进的Y—W方程对TVARMA模型时变自回归部分系数进行估计，并计算残差序列；
Firstly, the modified Y-W equation was used to estimate the parameters of the time-varied auto-regressive part and the error signal;
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