带有色观测噪声的多传感器ARMA模型信息融合辨识  

Information Fusion Indentification of Mutisensor ARMA Model with Colored Measurement Noise

作　　者：李恒[1] 邓自立[1] 

机构地区：[1]黑龙江大学自动化系,哈尔滨150080

出　　处：《科学技术与工程》2011年第8期1668-1672,共5页Science Technology and Engineering

基　　金：国家自然科学基金(60874063);黑龙江大学自动控制重点实验室项目资助

摘　　要：对带已知有色观测噪声的未知自回归滑动平均模型(ARMA)模型,提出了一种两段信息融合辨识方法:第一段用递推辅助变量(RIV)算法得到自回归(AR)参数的局部和融合一致估值,第二段用Gevers-Wouters算法和用伪逆求解线性方程组方法得到滑动平均(MA)参数和噪声方差的局部和融合一致估值。该方法可用于语言增强信号处理问题。一个仿真例子说明其有效性。For the unknown autoregressive moving average（ARMA） model with known colored measurement noise,a two-stage information fusion identification method is presented： In the first stage,the local and fused estimates of the autoregressive（AR） paraments are obtained by the recursive instrumental variable（RIV）,and in the second stage,the local and fused estimates of the moving average（MA） paraments and noise variance are obtained by the Gevers-Wouters algorithm and by solving linear equation by the pseudoinverse.These fused estimators have consistency.This method can be applied to signal processing with respect to speech enhancement.A simulation example shows its effectiveness.

关 键 词：多传感器信息融合估计 ARMA模型 有色观测噪声 两段辨识算法 一致性 

分 类 号：O211.64[理学—概率论与数理统计]