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MA模型参数估计的两段最小二乘法及其在自校正跟踪滤波器中的应用
Two-Stage Least Squares Method of Parameter Estimation for MA Models and Its Application to a Self-tuning Tracking Filter
【摘要】 提出了滑动平均(MA)模型参数估计的两段最小二乘法。首先用递推最小二乘法对MA模型拟合一个高阶自回归(AR)模型,然后再用最小二乘法解一个不相容的超定线性方程组得到MA模型参数估值。一个应用于自校正跟踪滤波器的仿真例子说明了其有效性。
【Abstract】 Two-stage least squares method of parameter estimation for mov-ing average(MA) models is presented. First, the MA model is fitted by ahigh order autoregressive (AR) model. Secondly, the MA model paremeterestimates are obtained by solving a inconsistent overdetermined set of Linearequations. A simulation example with application to a self-tuning tracking fil-ter shows its effectiveness.
【关键词】 MA模型;
参数估计;
两段最小二乘法;
自校正α-β跟踪滤波器;
【Key words】 MA model; parameter estimation; two-stage least squares method; self-tuning α-β tracking filter;
【Key words】 MA model; parameter estimation; two-stage least squares method; self-tuning α-β tracking filter;
【基金】 国家自然科学基金(69774019);黑龙江省自然科学基金(F01-15)
- 【文献出处】 科学技术与工程 ,Science Technology and Engineer , 编辑部邮箱 ,2003年01期
- 【分类号】TN713
- 【被引频次】10
- 【下载频次】374